{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3333\n",
      "95.0\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f20782b8588>]"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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J/5+zKgJIN39b9H0eqVYJpLxhevpRZgD0O/bec3jOccgZBt83NcVL7TYPj41po6+549hsFmC3qN22bfyFECZwGrgipfxeIcQs8PvAJPAN4MeklJ3tvs+NZpTeOtDV3z9SrW6olNkMaY952feJpFzX/+dmq2SGzQAYdOy95/BEPs9516UeBBzIZtdULms0dwKb/V3uJrXbTnj+Pw28AFTUv38J+PdSyt8XQvwq8BPAf9qB97mhDFPa9OrvAyk3PXVr2NU+7TED/IuDBwnpbu4u+X7SZ/9mq2QGrflYNsv1XI4HSqU1x97vHD5qWdvycnaLl6TR9KN3T6vf73K3qt22ZfyFEIeBfwj8AvCvhBACeC/ww+ohHwf+V24D4w+DlTb99PdTtj3y1K2Nrva9HnM8Keu35ub4+uoqAnh9sUjBNG+aSmbYHkgjCLjseUyruoJh+wzbye/vJi9Jo+ml5vt997R6H7Nb1W7b9fz/T+BfA/Fcv0mgLqUM1L8vA4f6PVEI8VHgowBHjx7d5jJuLKPo74cZpUFX+7RHkH4tgNONBtc7Hcas7kfkq2gjPRe3nypopzzlfrn9MVVANkgFtNPsJi9Jo+ll0fc33NMa1IdrN0SzWzb+QojvBeallN8QQnzHZp8vpXwMeAzg1KlTcqvruFlspL8fRr/9hH5ebazPj73rlx0HCWSF4N5CYc2+Qj9V0Lhl7Zin3C+3/8GpqYEqoBvB7Vw9qbnzib+fw/a0BvXh2g1OzHY8/3cB3y+E+B4gRzfn/yvAuBDCUt7/YeDK9pe5+xnmcceRw8uOw6oy6tA/h5/W2LfDkAnb5nXF4poePrB2KlisCrorl+urWBrmZQxad78K4Nhridcf5zi3o3IY5bztBi9Jo+llO7U0u4EtG38p5b8B/g2A8vx/Rkr5I0KIPwJ+kK7i58PAJ3dgnbuaUXPTT6ysbJjDT3f4fNFxOGmanFMTsdL0mwo2bllrvAxLiKHr2mjdgyqAn2w2k+rfUSd1baaOIs1u8ZI0mn5stZZmN3AjdP4/C/y+EOLfAmeAX78B77GrGNSPP74v3uVfDQLGLAsvinjVdXl4bIzXF4tJOiet44/n+95bKPTt8T9uWfz4/v3Ug4CT5XKS80975ksb1CP05iNfdhzGUh5KP6/lbLtNKCVCCOq+j4A1M3/Tj91I5QDQCIK+8wc2s3eRfmzvGu40tPpJs1PsiPGXUn4e+Lz6+xXgoZ143duFfv34n2u1AJKumo9Uq1Qsi2ebTV5xXQBqQcBSEHA8n++rCjjvuiP1+B+31n6MTzabhFLiRhHtMOSJer1vPUI6H+lGUd8uoL1eS7wX8KV6nXnf50urq7xrbGxdlPFItdp32lg60qmr6CHet4jnD2xG5ZN+rBtFa875naYO0uonzU6iK3x3gNhDTtcDPNloIIET5XKyy/+R/fs5ls3yyaUlmmFIxTRZUXsAtSBIOmi+1G5zznHWRQDDevz39uWJ7zuWzeJL2VeHnPbsN+oCCq95nQ+USqwEAe+fnOSq5/Hw2BiBlOuqe3tVDvHxnFAXoEXfXzN/IJCy7zEMU/mkH/ukmmR2dz4/0iSz2w2tftLsJNr47xC99QAV5Y337vKfLJf5vfl5LrguBnAwk+GJlRUiKTnTbNIOQ15UBj+uJt6ox/9Uj2feWzOwGAQD6xFiz36jLqC9HvaYZRFIuUbl0K+6N73/EEcC512XR5VkNZ4/kK4X2IzKJ/1YSwjOuy4X1N/DJpndjmj1k2YnEVLeepXlqVOn5OnTp2/1MjZNb/615vtJvn3StpPK3Ng4xh72F1QaZt73eahc5rrvJ/sFk7bNJddlXyZDMwx59/h48n7plM1mOmum/10PAs40GuumgMHgbqJxb/9nmk0OqnU+PDbGkVxuqHKnN+f/2Vot8Vq/s1pNpK3xdLJ0f6Kt5PzjcxtHEt8/NcU9qibhTkHn/Hcnt+pzEUJ8Q0p5aivP1Z7/FumXo489297c86Rtr7nPEIKcYXC3ZXGyXOYztVqinX+wVOKztRrPq41VN4qYUB5fWkc8TEEwqMr2vOPwr19+mfMq6viBqSl+6tChxNj2eubx7XHdwVdWV5O6g4pa+7Bq3t5/9/Na4/v75bJH/RH1Ri+9kcSdxG5Vjuxlbte9GG38t0hvT490jrs339+b/35bubymUjfd/yadBz/vuvg7mOM95zi0w5BpFQG8mFIAvew4vOI47LNtJKypO4gVOYcyGSLgnWNjXPW8dQqkQcRe0UPlMgu+n+T8Y9K57KcaDT65uMi7x8cZ32RfoN2sqdbsPna6Gv5224vRxn8L9Ovpkc5x9+b7e/PfvR1Ae725OA8+k8mseZ3terIn8nkKpslZx6Hu+0zbNk+srDBp2/z18jJ/W6shpWQ2n0/y5ZYQiSInlJIHSyWuet46BdJGapx0XUA6soDXctlPNRp8emmJQ7kcf760xIOlUhL1jOpNac9YMwo76a3frnsx2vhvgX49PWbzeR61rDU5/3QOe9Tulr3eaxxVnBgx399L+rGz+Tz/7vhxfvvaNZ5qt/mOsTEyhpFUC7+xWMSJIo5ms5x3HM40GjSjiKOZDDnTRADvn5igFnRbN40y2zf2ikqmSZCaONZbU/Do9DSfXFzkUC7HG5Ra6nqnw5tLpZGrlTWaUdmOt977+xsUce72/Rlt/LfAsJ4ecc6515vYag67Nw8PG1fFxgyqqn2u3eaS6/KfXZcfmJrixMQEz7Va3f0IwBaC/3D5Mpc7HTpRhACOFwoUDIMftW2O90Qyo6hxGkGQTBwzhOhbU/Du8XE+W6tx1nEomCYzmczI1coazWbYqrc+KGLo/X3fDvsA2vhvgUFX+nR+PK0z38gDGHT/sM6avdXE/V633/Mvui7tMOTBUolz7TZHslnGLYuHx8a4O5slBJpRxJlmk2nbZqHTIWcYPFgqUTQMAimH5tb7eUWxvv9t5TKe+jG82G6v87pm83k+NjubRDrjPXshG3VG3akf12732DTbZ6v7Q6NGDLfDPoA2/luknyefzo/HOvONPIBh9w/rrNmv8rd3Pb3Pt4TACUOudTo832oxadu81G7zW3NzSZ3ByVIJN4qwheByp0NEN4VVNIw1Cpp+xz8o0vhMrbYm528IAfTfy5jtkZkOUwvdCO/qdvDYNDvDVvaHRo0Ybod9AG38ec3T28os3LSXuOT7HMpkmMlmkVKy5PuccxwaQZDo42N1TaypN4UY6CFU7f6dNR+pVvnzxcU1A2X6eRbp5x/KZnm22aRgmnz3xASfrdX4zmoV2zBYCQIOZDIEUuKEIfO+z6PT0+RNk3HbZjaXG3pehh0LkOT822FIKwwpmibvHh9nzLKwhGDR95NjG1a3EM8u7u0z1C8aiPdeNjte83bw2DQ3lp3oNHs7KM/2vPHvp0YZpUtl+rnpPjqXPI/Lnsfri8WkcrdXH28JwS9furRGQQP09RB6O2taQvCni4t8sV7nonqvd42NDfQsjufzjFkWn6vV8KMIX0oiQEK3a2ipREEVRTlhyCcWFzGBuU6HXzp+fI0X3o/0XIFBx2IKwXXP44rngRAUDIMPTU8n8weGnfuNIqN+0UB6AtqpSoWP7N8/8o/vdvDYNDeOUSK/USOG3a482/PGf5AaZRSPr7evjIREAfS6QiGp3F3wfdphyDvHxqgHAU81m7SjiAO2zTXf53WFAkdzub7vkc6Zn8jnWfJ9XnEcKpbFPYaBIQQPFIvrUklp1VF65u7TqoXE901NcdXzeP/EBJO2zTnHoWAYfHppidcVi0l9wkbGv3euwOsKBd5UKq2ZNjZlWYRRxDvVmLtmFLHk+8kFo9+5j8/vJc/rOyO1XzQA6yegrWyyx89OeGx6z2B3MqwCPb1vt1civz1v/PupUUatDk17ibG2P1YApSt3Y71+7L3fnctxxXW5oHrxT9l2ohJ6stlc5/nGip/nWi3aYcg1z0s6g96dz/N0q5VU26Y9Xz+KEELwJmXMp207WUvclyddfbwcBBTVjIF4RsBG9M4VSLeXjqOCdhhywXWZtm2Wg4CjuRxPrKwk+xe95z5W9qSritMzUjeaL9w7AW2z3vt2PDa9Z7A7GVaRn/6c9lLkt+eNf9rT+9D09Eg5/7THEHvl07addKWM88xpbT+Q7CuccxzeNz6eaOe9no6Yg7p0xtHF+ycn+ezyMjnD4NvGx3m53eZztRony2XOOQ4XlNcfAQ3fRwrBffl8MnMXSCKDZ5pNnms2Oa46Yb5nfJyZTCYx4r37Iel9EejODHh0aoqQ7oUokJKaWv+ZRoOa77M/k+ECsD+bxVWpoZxSDvWe+/j8NIIAoTao31GpEAIPj40BXe8+3QH1dKOBKUQSIbyjUmE2l+NoLrdhzn+nvfRb5TluVVG2V+j9XHqr7uPPKW0P4v0oYOA5GyWa2K3seeMPm/P0+vWPTytlyqpn/qDXjb3Ti51O8vjeCuBBXTorlkU7DPlcrUYkJStBwKcWF5nrdPhmu83vz89zQnnVEd2NVgE81Wx2Nfoq9x33wLnuefzp4iIdKfn/FhaYsG3uKRR419gY76lW1+2H3JfPJ/sEhhC0w5DnW61kMtkFz1szv+CFdpsF3+eq5xEBc55HOwx5qtlM9inS56i3j5AXRcz7Pk+1WrxrbIxJ216znrgDajsMeabVWhMhvKda3dSezU556bfCc9yOomyv0Pu5DPvNxedmo3M2ajSxW9lzxn+zc2R77+/nicdKmUHVqzHxc+9VnSZj7xTgLWqjdFK9B7DOE5myuz144v78TzebXPU8pmwbJ4pY6nRoZbMcyGZ5U6HAUhDgS0lGCIRSH83m88k64n6u9+XzPB1F7M9kmLZt5jyPz9VqwGuTtgL1+Pg45zodFn0/ya3PdTpM2nbSz+hMo4EvJT88M8M3Wy0OZTI4UnI8n09mAPSe/5UgSM5PvE8S7008PDbGkrqQ3KfO36RtUzBNSqaJ2W7zULlMIwyT1x404QtIah7iCGIzXvpGapDeuQU3mo2ijb2Uxx5Ev72cYVX3o5yzUaOJfuyGCGFPGf+tzJHtd3XvzfM3w3DD6lVY630YQnDB8zjvuuv078OmaR2HRP0zk8lQNk2eb7Voq6lgLzsOC50OhXIZUwg+tbRELQgwgGlVjRyvI9b+u1JSMU2yhsFip8M1KXnZdRFSJnsGVurxzTBMVEtpzz+eSexGES+027zUbif7DkeyWS6rvH+6KrpfJJXeJ0nvTfzp4uKafkrvHh9PaggsIboXYvXagyZ8xaqs51utZG3AyPs8o3jZ/bqj3kg2ijb2Uh57GL2R+LCIf5RztploIs1uicT2lPHvdzWHwVOx+j0nPZEqneePc9aXPI+/q9fZr9Qp/XrYxF7u1xsNnChKZuGuBkEyiep6T9fMtKeQntMbzw34ZqvFk80mR3M5WkHAO8bGaAQBX1xZIWMYCCm56Lr87vXrvK5Y7A6JcRymbJt2FFEwTQ5mMqwEAY/XajSjiIplMW3bvGNsjB/dv39Nzt8SgiXf552VSjIeMj5f8bF939QUX15ZwRCCfZkMThgyads8WCqtUfQM6nga3x9HXIP6KfXbr0nXAMQTvmYyGb7VbgMks5RNIZjN5UZKEw36Dm3Gy74RHt9GCqXdqDnfDZ7vdvX8m40mYtLfkY2q9G8ke8r4D7qab8ZriidS9dOmA3x6aSnxTmOtfz9PPu4Mmp6Fe7/yHM46TlcTz2vTvHrn4aZ7CD1SrbIUBMx3Oix0OpyqVDhVLnPBdVkNQxZ8nzCKaEYRz7Ra2ELw8NgYl1QO/rlWizcVi+RMk6PZLM+2Wiz7PpO2zYemp9d9MYd5Luk9hTg6ebrZ5KLrJsf02VotOW+9s337dTyN6ddPaZD3lv7cLNFtJ/F4vU4kJTO2jW0YzHU6HM3luKDWtZ3v0Cj330iPb6N9q92kOd8Nnu9O6fk3E03ExN+RUar0byR7yvgPuppv5DX16uyvqpRPrzZ9JQhYCQLeU61y1fPWaP0HVe/OeR4Plss0w5C3KCPbCkMQgqJp8kq7zW+7Llc6Hd5QLCaTuNI9e840Guu84qrylj84NcWy7/Ncq0UjDCmZJvUg4IV2GwGMWxaRlORMk6uuSysMeV2h0B2/kCn2AAAgAElEQVQiY1m8s1JJKnDjyWQwPFqKz3OcV4/i/QUhyKn9AwFc87yuWigVyYzy2Y2iwuiNshphSEGpqwqmyT35PMtBwAOl0sAK6c18h0a5X+feu/TOwrgV52Ezn8VWOgD0VpnH75nOAKRnft+K78OeMv7Q/8o87GrdT2efzmWntem9Pf7TWv9+XuKkbXOl0yFQ3uk/2bePRdUu2QQ+X6/zqusmRvevlpd5sFTCUnnqJ9Q4SEsICsqop73iKdumZFm80G5TMAyudjpc6XQwgHHTpGhZrAQBEvhmq8VqEFAJQ+YMg7vzee5SNQRnms01Vcrp/P6w3OaTzSaNIOBFx+G+fJ6CYSDoXji+tLqaVDxP2oPrHHo/Jxi9q2k6yprJZDjXbnPR8ziay+HL7ryEQbONh7FVL1vn3vvPwrgV52HUz2IrHQB6q8zj30tvBiA98/tWfB/uaOO/1bxiP3XPuGXx5ZUVCqa5xsOO59jGOen3VKs822zyQLG4Jifd663W/G7fn322TUTXGy2a5poo47O1Gp7aoCxZFq0g4A3FIhO2zYxt40vJoWyWq57HA8Xiupm6cXSxEgRkhGAlCBg3zSS/fbJUIgSebzb59PIyJ/J5JtWP4rsnJhi3bf5meRkBrIQhZdNEAgu+z7cXCphASLd4bZAS4mA2y4KKWr5vaooF3+fNpVJXOtpnCtplzxuolkq/brpT6akRPtuHx8aYtCy+2W4n3n68vzBKJDHo+7GZ79VuzL3fbPrt3dzo8zDo84oVdsNqQTbTASCtWlsNgjVKuIJyqOK9vBOqJqa3X9XN5I41/lvNK/ZT98SdMWNvP1as9M6wdaMoudqnq26BvnrgV9ttPrGwwLhtkxWCD1SrfEsZQldJLy+o9gmhlFQsi4LyHk6Wy1xQksy442fveqD7xQ6iiF+fm6MRBBhCULFtvmtigpPlMvUg4LGrV1n0fc4pw/yeapWT5TK/e/06f6t6AnXUJq8BvNhuI5T3fiiX4xOLi3xsdnZNK4gpe21H0XK7ndQBuFHEmGUlXndaJeFG0UC1VL/XjTebh3lhadVP2tuPI6TNfE+2m6/eTbn3W0HscfebhXEjGEXhN2wNo3YA6P2eWcrZEnQl3S85TrKX54QhH0/V+Wi1zw7Tm9Mb5E3GHSlPqFbC/dQ9cW5+JpulFQRJpWyvCqe3A2fsHaS91acbDf7I91lWFaxjlsUbCgWcKOKZZpPF1PMfHhvjnZUKL7bbIAQHMxkOpX4wx7JZLmQyHM3liPp4I/Gx2SrXPmHb3S+klBzLZgGSbpzfWa3yTKPBt1UqPFAscqbRoBGGyXSvjEo1CSG6MwGiqCvDtG2WlPfe2wdo0rIomSYPVSpc8TyudzrMqrXGUUd83h9JrSXd6z/+3OKWFnfnckmvouP5/Jrq5n4e1KL/2oyFSMqkm+hGnUFH/V7thrz9rVDO7GT0068L642crwvD96zSx/iy43Ail6NiWWsUZdAtKEz3lEpXnb+uUOCdlQqNIOgKK6KIEPCjCClEovAbtY/YjeCONf7pnN4gbzLdkdISgo/NzvbNBVpCcKXT4YLKzacrZXs9+nQHzviLEXurfzI/zyuum7zfPvXajnr+XKfDK66b5ELjXHhbDVc5WSpxXalwPlOrcd3z+PLKChc9L+mUGZM+thXfJyMEtSBAKu3+eddlcWGBh8plLHW8Y7bNahjya9euJR1ALcMgq3T6z7VavOp53S+ukrhe830KhrGmD1Cc84w7jy4HAffn87ziOLzquol3NGHbXTUTJPsqaa1//LkteB6/Oz9PybJoBgH/aN8+Lrsu32y11lQ3v71SWedJ9Zux0BuhbCYPv9vy9rdCObOT0U+/LqwfnJrasUrZrSj8Bq3rI31+971V/nHVOXQzAXEjxedaLe7L51kMAvxGg+Ug4Eurq0M78t5o7ljj36v2+Hqjse5Kf061BjiQyXCt0+Gc4/DIxMQ6z2TR9zlZKlFSrY9jbX/aq3iq0eAL9ToPlcsUTbNv7v0V1XBs3vfZZ3d78f9YuYwPVC2Lq50Ox/J5nm02uTub5Yl6ndOrq5TV5ur9hQIFKZPeNxKomib7bBuk5EyjwbgqKlrTbRP48WqV1TDEFiLR8F/1PIJSiZ85coSnmk2qlsVTzWaSq6yYJm+vVJIq5IDul7xsGFQsix8/cIB92Wzivccs+j6rQcB0JkNWdR69t1CgatuUTJPzrouf0jl/oV5fU2l7Xz5PCLTDkDPNJuddl1YUsc8wWJUSqSqFzzsOR3I5OmoGgQCuex6/dvUqM9ksD4+NEagoI/7s4m6i6dYS/SpyB3mem83b32iv/FZEIjv5nvF3Jd2FdTOVshuxFYVfvK7rnQ4AWTXz4kyjQQhr5lbEVf5vVT2z4qrzewsFPrW4yLzvczyX45LncX+phJDdlupvKpXWVbrfbO5Y4w9r1R5PNpvrrvTTts0Vz+OC62KpXH76eTFTtk1ZjU9M5/tir+KpRoNPLy1xKJfjs7UaH5ud7Zt7vzuf55rn4am9g/2ZDPNBQM4wqKnxinHl6f9z9SqXO51uy4YwpGhZNIKAD01PM12pcKbZpO77PN9uc0k95qqKTj6yf/+abpuhlN0qXstKeub8ba3G0VwuUQrFa0jnKu8tFJLN4ZrvYwFnmk1aSjL6xlKJ75maWnesU7ZNxbJ4ttlM1DWXPI+CaRJBUr0b65zjnkEAhhA83WolcxAaQcDTjQatMOTFVouyZXU3xw0DL4p41fNY6nSYsLub05c8j9UwxAAeLJX432Znk8+uX/U1sOk5yaPm7W+GV34rIpGdfM/4u/Kikh7fWyiMXCk7KptV+EE3YnzZcTjvuhh0nbNfvXoVQxn+eG5FXOV/2fMoW1ZSdf5Su831TofVIODJRqPbvdeyKKnHx5XrN3rPYxh3rPHv9bj6XemLpsn3Tk4iRbf3TdE0+3pqg7zD+HU/ubjIoVyONxQKnFV59t78dz0IOJbNcvf+/ZRNk4plsRqGa6qBJy2L650OM5kMf7G8jC8lJcuiIyVvLZdxw5AxpTq4L59n0bKo+z62YdA0DJpBwFdWVnigWOS9ExP8zJEjfHFlBYOuJ9MKQ0LgDcUiXhhyJJvlgusyYdu8a2yMl9RM3yPZLKYQ5A2DC66bnI+3lMt8vl4nAnwpueC6vOw4HGethrlq23xk/36OZbP8Xb3O0VwOCTxQLBJCUhn9zVaLKdtGqB/4dCoyKJkmphAcy+W43OnwUDbLtU6Hf7xvH++uVrnourSCgBnb5qzr8t7xcV5yHBb8bhdTpGRFFbgNiwBhff4XXutplJ7FPOi7NYhR9522w04qiEY9rp18z/i7Ends7dcRd7vnaivRVyAl76hUeGelwrzvcziT4Uqn03duBbzWJXdcpR1Pq6ry47kc33IcPjg5yXsmJpiybS64Ll9cWeGgcoJuFXek8R/kcfXzUGey2eRxcR/53ucN69dStW3ePT7OZ2u1pKd9bx/8fnsL45bFb83NrakGXqZrMC44DkudDtc7HSKVo2+FIc0wpBYE/PXyMs+2Wt2xi1KSBa6qTaWyaSb59M/V63x9dZVWEHC50+GAkl0ey2RYDAI+r+oEjmSzFA0j6Yzph+Gax3/v5CQz2SwPlcscyGY56zjUfZ8DmQx/vbzcV8NctW1Olst8YnGROVWU5kYROcNIvP3TjQbnXTcJ+887DqfK5aQuwBKCScuiaBiYpsm9xSLvm5jga40G1z2Px+t1pjMZWmGIBO4rFFjsdHg+buFgmsnFelgE2OvF1pWmO71PsNF3qx+j7DvtBDuhINpslLKTqqWqba+T6+7U6281+kpH+3dbFg+Vy3yl0eg7tyL+XqXrVE7k8/xfly/zlKrgtYXgkclJ6kHAL1y4kEQUz7Va/NShQ7fXhq8Q4gjw28AM3amAj0kpf0UIMQH8AXAX8CrwQ1LK2vaXOjq9WvAzjUaigY/v7xcRDMplbqQtn83nk7z5g6US45bF6dVVoOvJ9E67Ouc43JXLrdE7x9XA76lWeaJe56SKQppRxJFslgfKZVZ9n6Jp8nSrRd4weKBc5n7PwzYM8qbJBc8jbxgs+T5/X68nRtWLIizDYMqyOJzJcDyfp64GrEzaNhMq4oilnEthSDuKGDNNrklJO4q45nks53L8y4MHOd1ocFVp959tNjGE4Gg2y7xSR5xShvZMo0HJNKlaFk4Y4kvJVKpDqBNFVAwDaVmU1WP2ZTIUTJPZXI53jY1RsSx+aGaGVxyHcRUxhFKyL5PhUC7HgyqP+o6xMU6Vy/zwzAxP1Osgui0sej+L3irhKXu9F7vo+9yXzycRYbzHk/5ujZKPHmXfabdwI/cObpYaaacmc6WnxMUFlsdyOT42O7tGGRjTr1dP1bKYUV1y4+/tORUdtMOQadumGYZcV91xbyvjT3f/73+QUj4phCgD3xBCfAb4CPC4lPIXhRA/B/wc8LPbX+ropNU1DZVz+/bx8aFdM2PcKOLJRoOKyu3X1A/3iuvyF60WWbXZmdaWn3ccPrW4CHTz2AbwiuviRxH3FAp8YGIi6YDZDkPOO07XmPrdtsVeFOFEEc82m7zsumSFIIgirvk+EVAOAiYsi79cWmLO92kGAVO2zfVOByEEJ4vF7iQu38dR+fhXPY+qZbHQ6XBWdfp81XEomyZLnQ7POw71ICBS+wk50+yqeES3rcRqGDKnNryeb7XIqvW/vVLBNgxKhsGfqdqHa50Ohuh2/fSUxvmP5+f5K5WDn8lkuDuX422ZTNIB1VWbr04Ucd3ziLJZGkLwQrvNtG1zwfN4vtXiSqfDw2NjzPt+kgcWQlA1TQqGQdEwkpkIsVF/Z0pBkZ5qdk+hwE8ePMiUba/zBu9RbaKhm+99UV2wLRURpr9bm8l3bxR1bJdBhnWzBvdG7R1sxvPuJ/kcdDz9/h1X4rajiB+dmWFcVbC7UTTycQ3qBht79I9MTKx7Tm+vnnYY4qgo3BCCFb/bSj3OCBRUajNKZRxuBVs2/lLKa8A19XdDCPECcAj4AeA71MM+Dnyem2z8q7bNA8Uij9dqlCyLC66bdM2UkPScH3TFjf28ehAkTdy+0Wx2m4JlMms09TXf53euX+dMs8lyEJAxDPww5KDyhNvNJnnD4KMHDvC78/OcbbX43y9coGrbHLBt7ioUuOy6/NXyMq0wxDAMTpVKFIWgEYZUbZtXXZffmJvjVfXDyBoGBzIZakHQ/YJHEfcVCuQMg3YUdds6mCbvn5jgdYUCn1xc5HSjwRXXxYsivqR67R/OZnnVcTClJC8EE5kMBt22yFJK9mcy/MSBA7ykZgZ/bXU1Uc0s+n5X+aMii4xh0FCtL37l4kW+1Giw0OngScl4FHFXLsf7JyYYU3rpc45D3jRpRxFfXV3lgVKJl9XmdCsMaQUBX1hZ4ZIqZJvN5ZjOZHih3WbSNHlrpcLPHDlC0TQHNtt7S6nEqtpQv+J5tJtNfmduju+enBzqDfYqhNKe/1bz3TuZJ48ZZFi3kuq4EeuD0T3vUaWVg4amxPUcrzgOS0HA/3vlCtPZLDnDAOBt5fKGU9161xsreTayF/G5i/P8c50OS0HA3dks/9PRo4SwJk30744f54l6nafUnIvP1Go3pfV3L8ZOvIgQ4i7gJPBVYEZdGADm6KaF+j3no0KI00KI0wsLCzuxjN43QEhJTkkN532fimUxZlkDvYC49Pyt5TI5w0gkZyXTJG8YTKlQrR2Ga1JIThAkjc/GDIOseu5qGFI0TS55Hs83m9hCYBkGQggsurK2ZtCdm2vQ/TCiMOSy54EQVG0bqdIOlpTYQmAKga8M5Ewmw5FcjiW/K3O8K5+nbFl0ooiO8sDHLYtmGFIPAqTyMvIq8nGUF162LJY7HZY7HUwhsIETSnWRMwzGLAup0i3nVa+hQ9ksd+VyhFKSNQxIvd58EOCEIZF6Tlt5X5N2d1LYbD7PqXKZknrdsmmyHAR0oogT+TyRep96EFCxLCqWRS0IuOS6FEyTQ+p9F/zXxmKmh87EJfjQVWMsdDpdSa8qbLvouiz7Pk82GiyryO6843C23aamjF/ZsrpRV59qzqo6jkFGLH6d3tvPNBo8q7qdDmLQ8/uRNlRxsdCw2zd6r2HHtVVGjShedhxecRxyKrJeURvt/Y4nLQWNj2/K7rYmXwoCJtXfL7RaOFFEMwioDTnng9abthfLvs+zzSbnlQPW79ydKpdxoogLrostBJEQHMrl+NC+fYxbFmfbbc6riPL1xSL35PPcWygM/YxuJNve8BVClIA/Af47KeWqSIUwUkophJD9nielfAx4DODUqVN9H7NVar7P080mWZW++K5qlQ9OT/ftrpem94saS84aQUDBNLkvnwch+NGZmeS5rTDk8XqdZhiyEgRMj42B73NXPs8LrRYvqjTQV1dXOZDJcFkVSfnKGO7LZHjVcXCiiLlOh7xhMN/p8C8OHOCPFxdZUYa9FoYAlCyLb6tU+P6pKV5RoeOS2guIvRyhDPwvXLhAIwh4ttnstmegK1k7ns8TRhEN5bGPmSZOEGAr+aQTRYwZBi86DgUVup4slXBV4Zet5KF3myb7s1m+b3KSC47Df7xyhYueRyeKaIUhjtI0u1JSMM2+Ho6kW/V4SamKPj43x935PMeyWRZ8nyUlO/22sTEi4JLn0QgCmmHIV1ZW+PjcXCIVjTeJ4xL84/k8x/N5HigW+WytRl4dE8CzrRYHVV+kSMpkPGVcJLYVL3iYJ/5/X7nCJxcXkVIym8/zS8ePr1OEbdZjH2RYRzG4N6s4bJSIIm72ds3zEmnwvYXCwOPpJwWt2jY/OjPD78zNAd2K20uex9dXV5N07yhtk3vXC3Cm0eBXazWebbX4xOIiP3PkCF9TIobec1c0TXwpeV5deJ5YWUmKMtORabymW1ksuC3jL4Sw6Rr+/yyl/IS6+boQ4oCU8poQ4gAwv91FbpY4JfFgschF77UBIfBa465+jbz6fVEHDQuJc46vOA6HslkOZDJccN1kaPi9hQKRkjNO2F054uuKRarKk4y9luO5HA9XKnxxdZW/rdeZtG38MOS853E4k2HCspLCkA9MTGAbBt9VrXIkl+PNpRJLvs9F1+W8664Zf1jMZpP9BEsI8iq6+ND0ND+4bx+rYcjfLC/TCUO+urpKSa1rJQgomybjtk0kRFKxXFfNqiwhuOr7nCqVWIkippR39PpSiVOVCufabRrqQhWng7woImsYa0rZ4yjr7nyeM80mRcOgmM3SiCL+QaXSlYYqLfXhXI7ZXI7zjpNERQudDiXT5Pl2O9kkfnOplAydSRua96o+Rp+r1WipGot2GJJXUWE8njJuM/2y43CqUkmev1VpZ/pYr3c6ZA2DkmnSCsO+cuDNbk4OMqyjGNybURyWPm/pPZV+a8kZBv/Fvn083WjwUM8M5mG/y/Txzebz/NeHD3O60aClnKuFTod6GLKkPP9RjrN3HzCkW38SCzaeUt1qS6a5ZujSou8zYds8rNR/9+XzrAYBT9TrSRv4dhiy2OkghUh+xzezLUea7ah9BPDrwAtSyv8jddefAR8GflH9/5PbWuEWsITgK6uryabK9U6Hbx8fT4aHDCsd7/3g+0nO0l7Tsko9LAUB47bNB5QU8bLnsc+2+WoY8qrr4oQhTzYa1IPuXN1nGg0Kqt3yXbkcBzMZzrfbXFXG8mA2yxfq9W57hiBgzLZZDkO+e2KCp1stXnScvqXlL6sq4mueh60KUuZ9n4Cu3OwbzSb//NAhJm2bF1otnmw0WPV9JHDZdZO0khtFFC2LS67L64tFrrguf7m8zBW1If1nCwuYhoElBH+1vNwtpjJNLnoevlpX1jBYVT2Mnm+12JfJrPPmrnvdnv4RJLLTliqRjz3x2VyOP11cXNciNz0+s2xZG05DuuB5nGu3ecV1ATBaLXID2kyne8xsRdrZ64nPZDJ4UYQbhms2/0Z5/jAGSSI3kkre6OKwrZy3ehBwd6qwcNjxDDvuU+Uyz7VaXHRdApWGaYQhWSH4vqmpTR9LumDSEoK7VTFnOwzXDV1yo4inGg1Wg4C/XF7mcDbLmUYDS+0Fvup1R7faQlA2zb7NGG8W2/H83wX8GPCsEOIpddv/SNfo/6EQ4ieAC8APbW+JmyeQkkOZTNc4qpx5nAc+5zhc9zwk4IYhn1OVrunNoH5KgrQKIe01AfzIvn3UwpAHSyUeLJc5lst1S8GjiJPlMkuqh34zisgbBhUhmBPd0YaSbsvXqkqHlEyT5U5nzeQwzzCYtm38KOKi59GMIt5eqfB0s8my73M09h4si3eosYpfX13lZKlEQxU6LQUBNt16gN+8epX7i0XaYYgpBNNqgzfucZ81DJphyIPlMpKuQf77lRXyQpA1TSxg2fepGAZF00yKqd4/MUEjDDGl7NYJqLYZR7JZmlHEpGVxRimpjufzPFKt8ueLi7ytUqEguv2Tvn9ykrxpJvsYDVXuv6rSPytBwEXX5V1jY5RMk/eplrgxg7z0OBq8p1Bg2fd5oFwmm46iWi0er9U4rqqwP1er8Z5qdcvSzl5P/KcOHeKdlQr1IOBkuZzkgId57MC6x/Q7vq1IKbe6wbvdKGgra0m/Z/zavYNVetf1kf37eaBY5K+Wl2lKyb35PLUgYGELufXZfH6NzDMusnzZcbgoJcsqLRw3gVwJAh4sl/nKygrHcznOOg6nikXmfb/rtEQRFZUeupWS3+2off6errPWj/dt9XV3grgR2zVVJHUkm028w6wQfHppCTeKWPZ9zrRaTFhWoi6A9e2X015n3HgqXbzzimpV/LVGg2O5HPUg4Dfm5mgrLf20bbMcBOSUHCwjBG4U0QgCPNVn5yurqyx0OlyXEg9oNptd71sVbV1THvWC363o/VarhQFc7nT4m+VlJm2b0sQEedPky0tLSUO1Y9ksEmgGAR1gKQj43YUF2teuEUpJQ3nPRdOkZJqccxyyQtCRkqJlUTZN/CjidKPBNdelrqqEIyBQP6R7lCc7rh4f57YXOh1spQK64Lp8q9ViOQg4mstxUqV0zjQavOQ41JR89Y8WFjiez/Ol1VW+uLLCbD7P+6pV/CjiiysrhFHEU6ptxIRlrRmU8cTKCrBeyht/J+KWGK+4LkXTZMy2mVXrfsV1uep5/L16jXOuywXPW/NZb0ba2e/29yqZ4EZjMAdFHL3fzUG3beYCsBnDsxNR0GbXMqyJWnoUaG80D9226t9qtbjkujTDMPmeboXZlLb/vONwutHg9Ooq9SDgaqfD28plPqT2FQ9mszSCgLxp8rLrMu/7PNVqcX8+z0Uljb5ON4K9Fbn+mDuywre3NDudWzvdaHQbodEtMrJUmL8SdIet14KARhBwMJvl6UaDP1eFGHGx1DdbLY5ls8kA9G+2WtSCgP2qlWv8GoGU3J3P0wwC3lws0gGcMGQxCNhv21z3fY5ls+RMkxnb5lnV6uCS5+FJyYRpsqQ08hnDoBNFtFWxllDppnHLomIY+FZ30Pp13+ewSvXsz2SomCYdJVs0gDnfxwRQP6TDuRzTUjJmmsxkMnSkpN1scjCTYVmtr2rbLHU63J3LMWaaXFBdSaczGfwo4gOTk/zwzAyBlNSDgCAMCaXkLWqGcJZuO4eaSi1FUuKFId9qt8kbBtOZDA2li35LqcSLrRbznQ6TloUpBAfUWgzgSC7HjG3zfLudfG5znQ6Tts3+QoHPLS/jScnhTIaFIGBGFY/VVUrupBoc344iThQKSLoXn6Oq4O4fjI+ztLDAhCrOWVGfY9orrQcBpxsNpm07kZkO80D7MYpX3G/UIaxvRbESBNsaiThMW59+TPxeO+XNj0q6wDIeprQvk6Hud2tammGYjDXtbdGxGgRMZTK8CcgbBj+ybx+BlNR8Pxki1Fuw1XvM/dYeqAi5aFn4QBRFrAQBzzQavL5USga0nCyX+ZvlZR4ql2lGEW9R0eas323p/s5KBVgf3d0s7kjj31uanc6rTds2876PG0U4SsO9GgQczmZ5YmUlaSjmKfXNfqV9j+juzAPUVOHYS0q2dcF1OZTNJj173jM+Tigln6/XMehuGF31usPSV3yfmvriLirPuGrbXX19JsOYZbHk+92NKimpOw4CKBkGvpQgZXcWrmHwopr1K4B6p8Mltb560B3ass+2+Y7xcRY7Ha56Hq6UBHQvQhHdiVwHMxkeLJf5+5WVbv49DFkNAmwhuOh5TNs2C77P5U6HjtrA9aOIRd/nwVKJH56Z4Wuql/nf1euccxzmPI/rnkfJssgaBq+6Lh2VmlkNAuZ9n9erugTLMMgJQcU0Oe84PN9qYRsGrTDkmNo0/5XLlwml7Eo9hUjGQa4GAa8vFgH4k/n5bm+fTqcbMRkGf1evkzUMMkJwKJvljcUiZ9tt6kHA47Va0sr6ZKlEwTSRUjKlUnGrqstoul9R3KYjzvW+b3yci6mhHBvtJ6W/n8O84mGjDtPP6zc6dDOe5DBtffoxvZ73dr35zRAXbMbDlHwlorja6fCJxUXuVvn4fmNFLSF4rtVCyu7Eu+faba76Pst+Vw1oqHPYO4hoowhnyrYpmyZzrktD3dZqNPifX32VH5qeZiab5dHp6eT7FRcLfs/EBM+0Wklrh7+t1Xha7TvdrHbcae5I4z/M60iaudHN+Z9KtSyOy+8X/O6Q9inb7lb0miZHslmeUf10sobBS+0280HAqXKZmt9tE/y6YpFIdhvE/ctDh/j969c5msux2Okwblm8WRmq865LNptlTnW6PJbNciib5c2lEoezWZ5pNPi969cJfR+hvP4x2+ZgJsNSELDi+2TVxSBvmokXPqE8YVsVgR3NZjmRy/GK47Avm8UCFjyPcibDTCbDftvmH01PUzJNzrouQggC1yUvBHcVChzOZBJv5XVRxFXVPkIIwZzn8YPT0zzTbHJ6dZV9ts2cajVxvFBgQUn2DmezuIJh6AYAACAASURBVFGEreYCFA0jmXJWMAyO5XKUTJOsEPze/DwXPY8Z2+ab7TaHM5luiwl1ngG+bXycD0xMsKy8t7vVnIALrsuxKKKl6hmmVcRgGwZTmUyyv3E4l+NILsfXV1ep2ja2EMx3Orx7fJyjuRwfmp5OSvp7PeEzjQY13+9OWHNdWn32k0bxjKv22kaBsNb7i/cnTpXLzPv+mra/ve1ItjMScdFf3065t/lcb5QSK+dG8VQHec+9A5T6Pe9ltc9TsSweKJVYCQIOZbN8fWUFhOBNxSJfXF3lwVKJCdtet66nGg06UcQbikWO53Jc9DwaYcibSyVeaLVohSFvKZc56zicaTTWDGk53WjwartNzjQRvKYMPKOEHIdzOQ5ls0xlMogwpBOG3QLLMESK7tSv040GphAcymSYUXtqi75P1bKIcjlyQnDB8wiAd42N6QHuO8kgr6O3mVu6ZXFcfj+TyVA2TZ5vtfCiiHsLBf7h1BQ+8HXVZrilPOTHl5e7Gvog4JMLC8zm892BIbkcbdUqIs77P9VsMqF+aNdV4ZFQaYOaKoR6rtXiy6ur3fRTFGFEETkhsA2D5SBgwfOoqalAgm53zUhKxlTfoVUls6z7PkXD4FNLS1zwum2PbcCTko4ynBOVCg+PjwOQn5tjqdPBD0MC1b98RRWzxa0OnDBkPopYCAIiKfnNa9eYD4IkpVMyzaScvqiqanOGQdk0uTef7252qXP3ouNg0pXQ5QyDr6yusqxaWM97HiFddc4Vuh7cF2o1ZvN5/rEqmImjjU8sLnJfPs911c7aVQVunSiipOStc56HIQSrQcCXV1eTVFNDtX5+SXmLi0HAoz3DXmJqvs8L7XbiGBhCUFSeY7yfNGor4nSjwOdaLWDtPkXvAJrJ1Ov0fq9jlcxW2gNP2WvbKcfRb3otvVHKKFWy8TH28577NTns9brTg4Di/SFbCD6nRor6UjKnfj9PNZu8a2xszbqeajT45y++mOzrzZVKlAyDehAwbXeVV3Oq7UkoJS+021xX2QAgGR4Uj1d99/g4fzg/z58sLLDsd2tqQilxoggvDAnoypq9KKIWBLyk1hY3Srzseby+WOSFdptlv9umBHW+vShiWmUqbnb+/441/v2IPYoZy0pKrtN52jiPH3uU75+YSLwP6A4Bvzub5ZLnUQsCypaVDDgfVxWhR7NZlnyfWhB0m4MB7aA74LwVhl2tv22z6vsczeeRUvLGYpGrnsdip8OzrRbXfZ97SyXGPY+8afIm9cX+uqoOLSiPUwD7lDE4lsvxtdVVynTzmyEwnclwyXGYsLvN27wooqU0945qAxEoBcxPHznCY1euUAsCrngebygWmbFfa3K27Pu8pNJJx3I5UGkYQwimMhlWg4DvnpzkVcfhoudxIp/vditV4+xWlOdtA+8bH+eYKoKLm8uthCEz2SxvNwzOuy4zyug4UZREVB/ev5/ZfJ7Tq6trdNOS7pzUcctiwrap+z5vLZeZzeW6bS08D8MwmMxkGFfDb5oqejqYy3G23UYoj62f+gtINNw/efAgzzabvG98nNeXSuty/mn9ebw/MKwRWL8WAgAnSyUE3cE/S77f94K0E3n1B4pFJlWtRlzBnY5c7ikURnqPXi+/N2KII4pn1UUt3eRwPHXO4kpfSffC5ion6+2VCr6U3FcoJNOx3lut8orj8ICKqOMGfl9ZWSGQkvvVYwXdmpHFIGA2l+M91SrPNpt8aXWVCVUr0gxDnDDEjSIueR6CrsTTjSK+tLrKBZWqyRkGDVUz8FC5zPOtFkXVbkRKSVkI8ip1GALfVqnQCEMmTJMzrRYzmQwrQUBWXUidMEzWpHP+N4h+HkWs5oi9sN5c4M8cOcI5VeGbHjpyXz7PMyoqmOt0CKTkWqfD3fk8FctK9g5edBymLYtvOQ75Toc512U5DDHpeu1ZqzuQfTaX4zfn5rje6dDwfXKWRcb3qZgmXhTxZLvNoufRCkM8uh31JN12EAudTldN4zgsRxERYIYhBSE43WjQTHni8SCJC45D0TSpq6ItgAnL4qxqOFcPApaCgIOZDKYQvNBq8WyrlSgY9mUyHFMbwN9yXYgihOoseqpSobm8zGeWl0EI/nRxkScbDeaDgLrvc3+hQMWyyKvmVpc8Dym7RWw5pX0+nssx5/u4qk9KK4ooGAYT6kId57njVtUIQai8Nk95lG8ulfiPV65wVrXHrqgN5E4U8RVlJJCSXKtFxjD4o/l5DqpNvKwQ6/LfsQccSMkbSyW+fcCPtXd/oJ+H29tCANbn0Q0hklz8EysrAz3urebV0/l+XxW+valYTCqg057oRu/Rz8tPH2O6nfWySmnFmvlp216zp9AOQ655HmeVcMKNIgqmyT+dmWFRFRvOqDTe19T5+fLqKl9eXeX5VgsB7Fd98s85DlnD+P/ZO+94Oepy/7+nbj89nSSkkhASElqQHikiXARpCiJBFNQfiOWiNC9wL11RKYICgiAgoDSB0ElAemgBAqSRfnJ63TI7/ffH9zuTPScngUBALzfP65VXzu7Ozs7Ozjzfp3w+nwcvCHiwowMV0fMbm0pxY1OTGLlYKtHjeWgQ61NZnocF6BKW3OsKkl4sQij7bvNlaSeBKBXpikKT49DmurEcejGTQVcUHu7o4G0ZvKVkyfbNYhFTlihn1dZu9m/4ae3/jPOP6pt2EFDwfZEO2nZcp63Rdea0t7PMspiWzdLteTzQ1kaP72P7vlDEVFWhfJlKoQPLJPwyJZmbY5NJBuk6rxcKDDYMGmRNeWwySZ1h4AUBg2UUnvc8pmezlD2PeT09pCWyRVMUhiUS1GsaGU1jSbmMqSiEEmM/zDDIS6fdIMsXtrxY0xLpoyEu8jAM2TaRwApDknIfY1MpFsiLWlfVePTjyz098Y1WDkMSskn6oWWJSEVVQdfxfB8vCBibTFJvGChdXTTIRvUI04yj75TskywuFOjwPAbLLKPL8xidTMaSt1k53WuwYdAgexYTqqtZZFmskfN+p2Uy9HgeC2TUGNXDF5VKjEmlaDAM3sjnURAZgBIKwlaP71OlaRRUlVpdJwQycpbBIMOg03XRFIV9Zc1VVRRs3yeh66y0LP7R3s6+NTVxZBqhODYlUxBFsP1HhD4vm+FRFrBbLseLPT2MlUzt/vvdMZtlhbwWIzz4RyFUNmX96+yV9f6IvV3JlP4owlz/e2sDyfOqqgHlrKEvLyajaawslejwPHpdl9HpNEcNHhwjt3bMZsXvpml9MpC3CgVaHIdp2SyNMkuJehc5Xef80aPp8n1qdZ2Xe3tZViphBwGLi0Vs36fNcTArSnaDZbZiBAEN6TSdtk1W09g1l2NwIsGH5TIHVlezNJnECgKUMKRJ9n9MRWGd4zAikSCradhhyPhUigkSRbZGwq6rDYNCEJDTdfKyLKkrCqultMnWyP8zsgZDkKQilm2TbF4eN2QIC4tFblu3jpd6erCAVeUy1bpO3vdZJlNCBQG/i4aOt9p2HGkDJIA1jkPJE8qhdhAwLJFgmGHQ7YshLGlNEzKvQI1hUPY8nunupkbXWWnbZGRNPC8nSPlhGEcaIUKzp81xGCwXCTcMKbhiQlcZcBEZhYLA/ycUMQSmzjBww5Be36fVcVgrSWdvFQq0Ow4v9vQI+WXLogAYgB8EfFAqUZLOvkdmHQCt5TKr160jKYktGVWl2jBYUiqxxLJw5PbrZAkDz6NdRlceQjY7p+t0um6chXlhyE3NzRCGuG1t1EiUVbvr0uw4FHyfNeUyjbYdZ2d+GJJLJLi/vZ0W28YKAhZLcbB9qqvpcBwcWSJLKArdkuXp+z49ihDXqzMMSmFISqKS8r6PHwTUmSZrHIc5HR1xU3FTiIz+0e+kVCoeEeqFIfe0tpLTdXRF4dRhw7i2sTFGfRze0NBnoEekTdXuuszr6mKXqiqKvs+Va9ZstFa+KRsoC6ms93uST/JxmdID3VsRIkeBPgzp/v20/ryYEYbB7S0tFCUCbVdfaN1PljyQqP9Qibrqf362z2QYappx5D8xnY4zsy7XZWGxyPJymTYpgT7CslhcKpFUVYqeRyqZpOT7DJffudt1scOQesPgw1KJOZ2dqKGYqjfCNOn1fZwgQEEg5rpdIRrZKFn9vXKRXiN/+25XyLBHpaCi76OGIa1SCn2BHI36edsX0vn3xy6vKpdFs9Uw2DaZxEU0ShsMg+WWRb2uo8qySCIMceXNkJTRt4u8wH2f7VIpllgWgaLE5ZvILN+nHAqMfVGmd71BwH41NRR8nxnZLNvJsoeuKPy1pYVeedE36Do7V1Whyyh1blcXpSBgQiZDu20z2DSpMcQIuC/X1uJLp9acSNAiF4AmOZLRDkMKslmrhGLgekpOtVooI+SMplGWvINXenoo+j7Dk0lWlsuMTSYxJUSyVkYniy0L1fdxEeUmG6FAaqoqThjiyM/0Q0EOUxUl1lMJAQ1IqyozczksCa/do7qaBstih3Sa1bJ8VmcYNMp5xuOTSdLSkQ5NJBifTvNyTw/DEwkmp9Osklo/ed8nq+v4nmABK4pCk+syxjQZk04zPJGgy3XJhyGTUil2zGYxZLltSiaDHYYsK5V4sL2dKlkDzqgqY5NJXpf13mnZbJ+afH8G+OuyAT0xnWaBVAvds7qaGsPgg3yeJs9jsqx/P93ZSZvjUCOjxP4DPSpRPG/n84xOJFg+wECgMalUnG307z1UWmUWsqpc5rnubg5vaOgzPrHeMOiQ2UDEwq6X2drHqfVHiJyB+AaVvYkoC9AVhXcLBZbJ+y6r63TJWdSDDCOWYdgYW7vy/ExOpwWTvgKlBQJBpSuKGLmYydBsmnQ6Dpbvk9Q0JmcyhEHALlVV7JDNsnd1Ne8XCtzV1kbecdg+l+ON3l6UMGRMOk2jVAbYu7qaToncSWkab+bz7F1dTUEGWuukQGOXROZlZQUgqetMTacpBgGDdZ13SyXGpVJ48ImYx5/WvnDOvz92eahp8mx3NyDJGYbQyFGAVsfhr62tKKGQHS76YtpUVE9fKyNBNwjodhxUVaXNdVltWViIKDayAOhxhUaNEwR4Ycg620ZTVZ7p6mJbif5ZJjVA/trSwr2trayQA1N0YGo2y5RsNq7Td7ouRVlyWVkuY0lUxv1tbXHdPQhDbMkWzug6hqrS6ziUpBSEBzTJtDyjqpSDAA/olkiXNtumLQzplVmMj7gQE6oaL5wJqUviyNcjc4GSrLWXfJ9uTcMJAhHZa5oQTKvY3lRVVts2wwwjdniNts0I06TDcWIOhA04jkO742BqGjOlAFuE9VYUhbSiMKezk2bJTQgQC4zj+5TCkCXFIj6woyz1RTXYOk1jVBQxKwqLLIsDa2uZ39tLm+uyuFQio2nkfZ9nurpQEMisJaVSHLkPpC0f9YU6HCceL9nmOOxfU0NJLnbPdXUxIpGgGAT0ytJjvUSfVCI9onr5OttmreMwqFymHAR9auXjpeOPBphUMl77ZyeDDING2XTt8TymWRZ/b2vjmEGD2EUSjbpclwfb2+Oe2FDTJKmqzKyqGnCf0Xsq6/VRCWkgpFNl1P5EZ2fMAq+R/IqmchkLUMtl7mtrY++aGsZspM8x0PmJkFqV7OjKXl1JlmrW2UIV1gfeKxRiZF9ZErXuamujzRZibUttmw7bxgIW9PYSypJqt4SdTpRclUGmSUrTyEgAQqvj4AZCGbcbaJdVBsKQJZaFiqgu6IrCCrmIf1Lm8aexL5zzj2qZCogyR6FASdaoGx2HA+vqGJdKUQgCXurqolE2Ayek0wxNJHCkhMI+1dW8JscQ7pDJUPB90hIls6pcZrjU4PHDkMEyshyaSOAFAdMlaWhZuczYVIp3ZF19YjrNy93dXFcq0Wjb+GEY/wAKsEDewG2StToqkWBFuUxSVQU0VEpBOFJiIaEoDJOY4wgRstyyWKdpNDsOvb5Pj2QxE4boqsrIRIKUqtIkJQ5yuk4pCEj6PkXfx1AUagwDXVHYJpFADUOKnodlGFRDDOuMUtgAcRFlpRLoaNls2y6dZn4+T5srhmwkNI3t02lMxNyBJtelQzaxV5TLNDsOY9NpAnn+k6pKGIaYqkqb4zAllcJQFKpNU8w4QEBATVUlKRE/GU2jWtcJ5KLhhGLugRMKFrMrnXqAIOrNrKpinW3zXHc3SVXlyEGDeLqriwNqa2l3HFbbdoxsqjfErOZojGQ0su+57u444geRUY5IJpmSTvNWPo8D7JLLMau2ljfzeb6Uy1EKQ45saGBhschOuRzHDB68gU7PgbW1vCXPX5WuU7BtvjV4MD6iZBj1IaJ5EyWJ5MLbkOUbcVvaPY/lpRKjK3TwK7ONXk/IeidUlUCeu2iIfaRcWYmO6/G8WN2y4HlMyWQGREpFFr1vZDIpSjuZDMsti4MyGd7I5+kKAgZJtn3Ui6qM/FdITH6NYcTnZ2mpRLvrsrZc5h8SlumFYQzHLgUBg02T3SU80w9DWuT11eO6TE6nmZ7LsaRU4v7WVtoch4Smid9S9sAmJpM4El49LJHAkcigDwoFdqqq4tRhw2Ll1hbfZ1ZtLR/KudxFz+OVfJ4J6TTv5fMst20mptO8WygwI5cjCEP2r62lRv/8XfEXzvlHtf0Xe3pi51EMgnjW7MyqKvaprWVBPs/Va9bQ5grpgKMHD2b7bDZm+L7S2ytgeIpCk23ztUGDWFsus6xcpkde+GEY4gIttk0+DCnK5rEHbCuHrHTJhajb85jb2ckD7e1xiqsqSp/IeJllcf6KFYSAAySBpIyMOoKAEMjL9LBULrPGshieTDIqkeD9YpFlskHaIdPngtxvTxCgAg2KgqkocfSc933WOY6QfEBE8iBmBxiIHofH+uhdgT6lrgh15AOdvh9HtKaiMCGbZWgiQRmhK9Tuurzc04MH1BWLNHsegXz/MsuKGcwpTcOWztwJAjTJfWi2bZZJddS0qjIhnabX82iW2VYIqGFIICO1sty/pigUPY+3i0W6HIdVjkPRE0qji4pFqnQ9Rrlsl0qxjVwcs1LKIoqWU7qOE4YcWFvbZ2RfhAAD0WjcTSpKvlcs0ua6TIMY751QhOZUxAyPILXRnANgA+TLslKJuRJ+GjFZW1yXZTJjiZRRGyV2PC0Xsf73xJBEgrQUzItq+/2zjSpdx5V4dVXXSapitkT0/SLlyv7ouOi7ALR73oB8g/5KuBlNY7ll0WjbTEqlBHihXI6hv2/m86ySvQFNUdgtl+sz+Pyg2lqsIODxzk5cX8yO2M2yeLqri1OHDYtVbhttm1bHIavrlCU4o8t1QVGo03WsQKhwviPRbO8Xi5Q8j+4wpGDbaMDoVIpRySRFX2hUtZTLdAYBGvBwZyczslmqdD1WANhGThAbZJqoisJ06eRLoRBPXJDPi56Y1Moan0rFmdhWktensFrDYKdcjme7u8noOkWJNMnpOnW6Hk9zWm5ZNBgGY5NJlttiAElGVVlXLjNOsnITqoohMfNpVWXbZJJezwOp2ZOVaa4KuBJt4ISCDLVSykl7gdDQKXsei0olgS03DBzfZ/fqapZUyDPndDGxSgdMAEVIGRiahiNTSRDR9gjTpN11cSTpJUCUqtKaRllG9KtsmwSiPj9E19mpqooJySSdvtBDyXteXGd3goBB69axduhQrCCg1hBa6NHCEI18a5B8hm2SSdaUyzi+mAEcKWsOMU2KEoa3Ry7HpEyGuZ2drJYks3bXxQrDeCGJ9DjTmoaHGDYzNJMRGUcQUGUYGAjCV1rTMGWjt9XzmJROU/B9MjI7GG6aFDyPnKoy1DRjvSBLpvS278cM7CAUJJ1JUt4ChHbQxFSKFbZNnWEwzDRRgMXSiRAEvKXrDJHZ1yjTZLDMdCKegReGnDlyJC90d7OsXGZqLieQZZ7H3tXVdEusuSrJWSVZsot6CVEkvUpCHQ1VRYWYyJbWNHbMZllSKtHhuhwzaBDzurro8IRgXjT5Dfqij6Kae/+5FJVWifkfkUhQbxg8393NGtumWtdxw74s5lbHib9L0fdj8tOHlgX99IL6K+H+YPhwVts2a8plxqfTlIKAUabJCtumQQ496vV9pmazQnDPFxP0ajSNdtlAjq53Xzbxc5pGq+ypbJdKkdGExHiDYeBLlNhhgwbFJZ69a2owFUGgHGGa2LI2v7BYRAsCcpJdPy2bZXI6zeJSiVIYUnRduoMgDszW2jYj5fWsK4L9PiWTYbjMDqdnMqyxbcakUsysqmJ+b6+4ziXPIzpvWxm+W8AaDIO1tk0gI+GUpmGGIW0SIlnJ1lwoO+1rLYvbfB9FVUlH5BIg9H1MhD5+s23zZj6PE4ppVqokfERliCgbaAOoaOCscIU8cZWiUA4FO1FTxBCRfBDgBwFlwJaIgAi1o4chHZ5HwvcpSHRBpBVU9cEHHP3SS/z6W99irWTE5n2fNGDJ2qTL+qi92/d5uadHkG00jaXFImX5eui61La18fqxx3LnAQdw8nnnEcgFxZfbqAgUkC0Xm8WFAg5iISq4bpylrLUsuuQitbhYZGgiQRCG5OU5cBH9gcqMx4dY09+X9fEqXWekdDBRqaXgeRQ9T/QsPI/Wclk0732fIrC8XBZzC1gv2rfUsmLEFuF61JQmb/oV5TIL8nkWWxadrssD7e3UyOxRlVlSo23zSm8vJc9jfj5Pr+9Tp+u0uS6jy2U0eV6Wy1nRkd5Qq+Nwd3MzKyWM9M6WFg6qraVK13m1p4fl0sFPkKxwII5YF8sRgSWJAskHAeOSSVSIlVejpuwqGd22OU6s7zMQ9n5jA1UG0vjZp6aGbs/j4Y4OcY4KBQ5vaGB8XV3MYo6AC2/l83R5Hi9JGfEnOjtj5E3El+jPFJ6RyzEjl+PW5mbuk7IeSel4k6qK5ftMy+V4pbeXUckkkyQhcnGpJGY8+75QxZVOPaVpvC9lGyLWeKSh/3x3N8MSCZpsmxpNY1GpREn+rvWmyaF1dTQ6DiECXTQ+meR9+dukVZV3CwWe6epinQzofHnNlnyfJIKT0eK6rLUsXMCU37PZdclKOHWlNtg2iQRdkksTnbc9q6u3Mny3hNlhyNRMhipdZ51tMyaZZFI6zRLLYk57O9tL6N6RgwZxa1NT3MT0ET+cKqOtGvlcvS7m4Pb6PmlNI4MYpxhp51jSgXcHASlF4d1SKa6HV5qqqqRl5Dkpk8H2hSbI+EyG1eUyjmxMLv7Slyglk0x++mnsMGRMIsHSUglVVeMh7fNPPhmARdtuyxN77kmIcHoZXScZhhiaRs4Xg9BdYMrq1bx04ons9OijNNXUoGsag1SVkicmdw3OC4mqbz39NOf+938zJZ0Wze5QjIkkDKk2DNGElWQYPQwxgILvk9I0hpsm3Z6HJZ2sF4Y02TajUil2zuVE0xJQwpB3SqX4vESN+YLnMcw0Y2hqrURYDU0k2CaR4Jnubsoy0tMVRTBQk0mCIMAtlfBlWSulqgwxTVLyfOnS0Y9KJkVJA5FhjJS6Qj2+z6hkMoaGDpL15cGmyVDJ0h5uGKyVN36I6BmYsoeihCE9vh/jzJeUSvR6HkMTCSzfZ6hpMlVqyuyUy1FjGLxTKDApnSajaYyRUNceTwgM2r7P8lIJU2aeoYzkx0v4aFJVObi+Psb9J1WVWbW1vNbbS708hnbZa4mmTd2ybh3NjsOMXI4vVVdvoGXT4jjC6QYBzRLVtFIO99mvpoYPikUmy/nLlSzmCG+/d00NTbZNtaaxUE5zq5JyHx9aFtWyJLbcsqipQAFFCJtQlq902SxuBjz5W41KJGh1XUYlEvS4ggSpK0J4cGIySbvMqtY5Dj2eFy8GkfLqhx0duEGAHwpFz0pUnx0ErJNZ6YhEgr1qapiWzXJHUxNPdXUxUfZu8p6HqesY8r6eapoUAzF1bkQyybpymUdknyGSYfeCgJHpNM90dYmJd5pGq+PEkO6y77N3dTWGqm62LtOWsC+k8x+fSlEdwdRMk8GGwbNdXbxTLPJqby+jEwl2raqiw3Fos+2YNZtE4NsLsp5XlOWJ1iDgrTCk03EoIZxVqCiEsomaDwI6HIc6wyBgfe280kLWR7weQiNoSiZDOQhYJ/HAFtDe2QlAulym2XV59ZRT+MNRRzH/4IMJfB/64YHv/eUvOeDKK3lm551RCgXGv/ceT++6K2nPgzCMv9tLJ54IwJuHHII6b54YlCJRT2XXZd/Fi+N9tjsOr7ouxciJI1Ja33GY+d57vHT66ex5/fW8PXkyefl6yfdptSyyQLHPFxcwynpDiMgtL5XiRmilrXMcPECRqpzdMisLgVrb5nHPIwwCHIgb77qisFaS4IoIuWhCQWgbJnkCq2wxM9lDKKvW6DpIx9EhM8GRySRNtk1GVbF9n3fzecpBQELT6JGRZpu8We0gYHmphKGImQfVuphhsF0qxfJymaLnsdiyaJGY8sGGwbhUirW2Ta0h2KVzOjpYKjONelmmjBQ6l0muRJtEekWNbTsI+FtrK7WGgSnRPkMSCQHfLRZjlE6njChn1dTEWcT7xSJNtlSXVFV2q6ri4Lq6eI5sEIZ8UCyyRta4/TCMEUWRMmWtYTBDlscGwts32TaKPM457e0godDD+qnlRr2PKCOolzyYVeWymDkRhjTbQr9qsWWJkaayzm/JIMOQi35aVdE0jTGGwTeHDOHe1lbu6O4WKCLD4GsNDRQ8j0bLYo1liRkVspQTZbNtrktjuUwAjE6nWWXb1Oo675RK9AYBj3V04IchJQmyyEiezmrHQVeEOFtG13m1UKDseXSFId3SfyySvZ+i57EUIbtiBYGYMAYYqpgpPSOXo3748AG8xmdrX0jnH03eeSufx5LpXYAYK1jyfZZaFhNSKfwwpEE2Z1och32qqqg3TVaXy5iqypv5PCn5Wo/rkjEMDIlln5RKoSpiKEutplFSVYZJiYSEPI6IFKUj2LfDJXGoVtMoeh5532fHXA4Fka20lst0VNTLxQAAIABJREFUHHpo/D3q83mmL1vGDVdcwfwddqAtl6OxuhrT6es6nz7zTMx58/j9tdcy+/HH2eH227HGjcMNAsx8nmOefrrP9rr8ZyhiRm+75/GXyy+PX8/oOiXZMAXifkJDTw8vnX46AH+96CIOf+ABlkY6LIgmdfS3hsiadMRFX6PrTEmnUcOQRZZFrbxJEvJ9uqJgIkp2w+Rv0uW6+NKhhGFIrWTLGoqComnsJrHd3Z5HtaahysVh/9paDquv55WeHqwgEIuDbBQnVZVCEFCr62LMJQgNI+m8vlxby3ulEoQh26dSfFguMyObZVw6jR2GaLKMMsQ0WVQqMSmdpl7XmZLJMDmd5tnubj6UTUvk9/nG4MExGsqTNfnp2Sy9nkedYfCVujq8MCSpqkzP5Vgu6+CeL4hyg2TfY63jiNq0PP6IcbxjNstyy6JKFxLaPZ6YWDUjm6UoFzNXgh+8IOBDyY+ICIA7ZrMMkQiiiFEbaT5VTrAaaOZwhLePtPYjGY6JkkWcVpSY4NTj+zToupjDYItpaQDTMhkmJpO8VSwyMZWi1/dZJKVRemQmmdM0LN+nStep0TS+PmgQ07JZlpfL8QS95ZbFc93dmIqQ8ZiQEjN0x8meQtRortF1ijLrbpVBhxMEgrVfKvH7tWtZY9sMk3MDRsnZGEEYMiyZpMVx+mD5W22btKqyfS7Ha7296IpCTvZ/AmBcJsNKmaFFmaMmf29VUVBho/pNn6V9IZ0/CKG1D0ol/tHejiUJUN0ybVeBUlsbuqLQZtuUEc5qoWUx0vdjlmqXJDUBQkdf1q11YH5vr7hoWN+0XGrbDGQhUCXT7yJQjJp7pVIsHesHAb393lff1hb//da3vw2AMm8e+7799gafMXHFCo6dOxeARLFIi+dRbxgs+upXN9j2t1dfzbnf+x75TIZeT1D7K23qq68yd+ed+zznAZfecEP8eHRTE4ssK17gonykWPF43k9+wo4ffkj9ww+jOQ73tLayTs4diBA6cd9AljaiGQJpVWWpRGUYYUgZEW2FQIvkKLxeKFCtafTIBlwAsc7KO8Ui3a4YXxlFeSF9S3E5QFFVGiWKyNQ0XpP79oBGxyGjCCZ1qAh29R5VVTGXISP7Q4stC8v3eaKrSwQbloWiCinwesNgWjbL/Hw+Vo7UZdCQUFUmZzIxOqYcBMzv6RET3SAu9zQ5Dn4QYAVCl6hK01hp2zzY3k5ScjcihmukQhspjHY4Dr2emOJmyb5Rm+Pwt9ZWGgwhE77MslDCEEX2oSqRQGMGcPqRVc7ejbYpeJ4oH4WhaGb7Pi91dTFIcjmSso/SFIZ8WC6jhAJS2uy6uIFQxcxqGpbrslpmryHQ4nnYiJGnSSmJsUg2n6MJeg2GwcpyWbBlFaG9UyPlQ3pcoRUV6TONSSYJEU43DEPCIGCVZUEYsrRUintHiqKQ0XXsUHCEuj2PtbbNWomuUhDT8aJ+VICoGNiuiyGvI0ue/7Ls7UXmeh4FYGm5zBOdnR9bMXVL2RfW+b9VKPBsV5cYewgEqkoyEESZiOFbDgLSuk4oWYWW79PhCfEyU6Zobhj22W8G0dh05L6iCDfc8BBEJKtpJDSN0ckkCwoFZi5ezCunnsr4O+6gZZtt0FUheWyaJt/7y1/6vP/d7353g33WqkIXv78tlD0AgMtuuYWzr72WcYnEBtsBnP7gg0xZtYr/+v73adtxRwxV7fP6M2eeSfaZZyiqKhrCYRrATsuW9dlOUxRqFYUe2eBVwpAdPvyQd8aPxwhD9pOL1BDLIshmaZRRu4lIn0Pfp9o06ZSRYaQPM9g02T6Vwkb0YNpsGycM6ZaN7yizsDwxGrPeMNBkaSarabTZNoqqisEziBs0pSjYsowXNZ5DREamKgoJXY9JcAlNw5W9kAnptMD56zpKGDIymWRGEGAoCjOzWRKyxl4MxKS1Gl1HlXpDh9TXs3tVFQsKBVpsm+lSuXPv6upYMRYEpHZcKsXYZJLnFIXt0ul4olydYcSEv8GmSTkMGSmz0+WS9GcHAccNGcKXqqpYK5E5KyyL8ckk3a7LlGwWLwhYaFk0SI0jXVUZn0pRp+soisKoRIK1cpHZFOFoQT7PgkKBlKJghSEjDANTsscjXP5hDQ280N3NQhnYDDYMdq2qQglDRkvE3DLLotcXE9w82bgdlUySLxbF8aRSlHxfzFwA2uSiklTFrIpH2ttp8zyGmiZpVeWfXV0839vLENOM7/EVloWpKEzPZmmRs6mHmCYtts1IqbuzZ1UVnZ7Hiz09rC6XSWmaUOzVNJQwJK1pzMzlRCMZYi5MVioABEGAKxd0U1WZlErxYamEoYmxqIbsQ0UowLJcgFOaFqvWDpU9rq1ony1gKyyLX69axSs9PRSQNXrEl41i3BbX7cNWtR2HBMQEMY310WilFUFABunLdh3IHESUWgO81dtLDzD7kUcAOPGJJ7jg5JMxfZ+cqtJqWVxx/fUf+d12feMN9njrrU1uc9D8+XyzXKaxvX2j28x66y1e+MEPGPfSS1j+ht9k5Jo1TFy7lmd32oneVAoHeGbGDGYsXRpvY4UCuxzZKY88wo2//S0H/vrXvLjDDvHzTYccwonnnce9++3HiY8/zs1f/SoeovaryFKEA/F0rl7fpzcIKPs+K6R4XoRMQv7vIcpqBcnTSCJRQ9F3CQLxD/HbF8KQJPTpNeRZ3/dQgJLcryPhuwUJDS3IoKDJEfOS1zkOHa6LqogJZLqiMNQ06ZVEKV0Rcr27V1XF6pERDn5Ihe5+JcJmTDLJQgn7XW1ZpGRjv8N16ZXlsXbXFaQ838csl2mUJQsNWFIu87WGBlZaFssr9OK9IKDb9wnDkGESltrreSihwJwPMU0WFovMz+fjvtV8qZHff6pXpJPf43msKZfZJpXC9n2OHzqUFeVyjCjqcl3m+D5v5vMxakoJhTZOh2zIRoqubhCI6WthyJpSiTIiS4sy7FIYokq0V1FRKHkeS0slXunpoRSIIUdVmsbfJDFtrWWRNgzUMKSlXMaBeKrdqESCJZbFmlJJ9CQURSxYjhNrYxnSyRsyQwmAp7u6mCBJouvKZUrymtJkpB/dPSoC4VYCkr6Qoh6VTDI6lcLyPN6XfYe0qjLYNPlADod6o1Bgei63Fe2zJWyZbKYlNA3X99ERUWqkz5GRUWCP/PF0hPTAiGQSW6b/Jc/DlSlhRJaqVhSCMCQto8RUYyNXXnUVx5x3HlY63eciiKJlBXEhlRUFLQz54UMPAXD+7bfzq5NPJqNp1EqRs49jT/zsZx9ru5svuICfnXbaR2635+LFfDBuHADPTZ/OvgsWAPDBSScBMO/AAznx/PPp9X2UfixE54AD2OGBB+iSrMo9ZdN4WnMzK4cO7bPtXy65hHFNTVxwyy0kEgn+dOCBYiCG77ONRLuMSCTIBwE1kgA0WEa9CmIgSwJxg0ZRO6zvLUQw2Khk099SwPRMhk7Pi2UvHNb/RiAQQPWGQadE6hQ9jx0zGYpBQKfnMUJG3kEoBPVQBHM6UiadmsngA+PTaWo1jac7O1lVLot5r6oq8PdhyJ3NzdQZQlcqKbOuV3p7aXYcsqpKSlXZJplknSNmGbuOw7ay1jxdauhEg2g0xPXV5bq81ttLgwQd2BU17v2qq1leLrNzNksxDMmqKu2ex07ZLFlNo12iZHzZB7F9n+e6umi2bbZNpRhumhCGPNLREZdlAgQDttf3eUdqGTm+z141NYLV7fuMTiRochwGGwZTMhk0ReGZri7GpVKkZVksa5oi6pd9gIIsh4UAcnFy5TWQVFXWyM9VVBUtFIJ9PTJgG5NK0aHrZBUFU9dpcxxysq6uKwq6qpKRvJkIAlsIAmx5HQSIcanbp9MoCBBCvSHGvqY1jZIM+nTW98FMeb0ZsjwYPW8oCoaiMD2TYadcTgjFSUHGdRLZl9V1ccySL7EV7bMFLCERCkVf6NHoiNpd2ReqjklNo11qiYCIIEMJcbNlnb+S2RpZj4xyHc+jDHQfeywAj511Fntfey0vnXYac3bfnUtkfT5y561ykVGCvuDPwqxZpJ56itYBIu9Pa19/9lnO/s53PnK7y888kx+ceSYAq/oxQwFmPv88x/z97/zlgAPY9403AFhXX8/wjg503+eqSy7h65dfThmYPWcOAF2qygP/9V8b7GubpiYALBk9AZRcl0bXJaeKYStLCwWWyoaroQgGtB8EQveFDX+T/r2G/vDayCzg3VIJTfYPou0ql9y1sv8RIobdp1WVl3p7WWZZhGGIHYakFYV8KHgdhCG9rovqCo0iNwwZmUiIMYwIVNI7hQK6IuYsF4KADyXRT1UUJqXTdHpCe6jVtmMmNgjOiB8IjSgd0YBNqSpj02nm9/Rgy2wpkK+pQUCLJHV1yt5CXsIam6V8McCuVVXUGQYZGYWvKpd5rVAQZTXPI6NpvJ7PU/Q8nuzsRJfQWU0R5LqCvIdcBG7dA57t6kJXVUYkEvy5uZmv1NbydqHAO8Uilu+zWtMYnkyytlxmpW1zX2srvjyfKUURfR25fz0M6XFd4TwRZExVLrgRW98F1EAw3tc4DiZQBjokiqwVsaAHgOn7cZ+h3jBYK4mJHqIUXKOqdEF8PZaDgCbXpdd16QgCVkqiY6vjxP6i0mz5Wbb0DVEPzJH3+uOdnbwrob8ZTaPLdWMxxyhrGGGa7CkF9j5P+0I6/3bXZWI6LSYTWRZDEgm2S6dpLJfJJpPkJEzN8/1YpyYjb8gaQ6gbaqwvE0VM1ADxQyf7fd5eCxcC8KX33+dL778fO3/kPgzggJdf5qFzz93gWL/53HP8+eKL+zx38Ukn8ctbb/1Y3/WPhx3GDx5+eMDXvjp//ke+f3hHBw+dcw4A2wxQJkqXy/z2mms45NVX2UVG9sM7OuLXD371VZKyiRaZp2nssHJln/10ZbNUSdZnQZY9BnV10ZvJ4JgmoYR3VjJ+T7n3Xl7df3/WDR5Mt+uSMwxWSzRVnvXSEkCcFdSqKj0SyheZhhgUY6pSt8Z1QUL+FMTCYCJ/Xxl5lz2Pel2PSXxJ6fSVMIxZxlFDT5HH2yNr+Kaq4ks0RyQF7YUCY25Lp+CFYczcjWZG2I6DoWnUSa2pSCJk91wOU6JUel03Vr9UEQtMm+dRK+WGU6pKSc55ADGnWlUU9q2tZa1tMzmdZlQyyWs9PTzX00NS6iFNlL2NIAyZ291NgGAbB0BZ9rbSqsogWbJQgZW2TVk2YjXZmO32PBpdlxpNY6iss7thyKJiUcyqME1WlEoYqpDQMBWhurltKkWzI8Z4LrMstk2l6HVd2nxfaFZJhc4aicxKaBqDdJ3Vrstgw2C1baNXXBMJ1sO3R8oZ3VWaRpUm5m6gKIwwDBK6zvzeXjHPAXG/FjxPcEYQFQMTUX5KQtywjUqFCUTGWPTETI2IABZZMQzFzI0wBF/oTGmyDJYARpkm540eHbPMP0/7wjn/iL3b4Xk0lssYCGnXtbYtGoS6GEjS2a+e31ZRI+5vG2QA/R7//ogjuKPCgR/53HM8uvvulBOJOIM45OWXB9x3f8cP8F+zZ38s53/bQQdx1qmnbtT5X3XddfHfyrx5/P2CCzj6n//c6P48Tdvoawe8+upGX3v49NPZ+5pr4sdff+GFDbapLRQ45tlnARFxAbQeeSRP7bwzB115JQVgiWSF+sC0t9/moquvhquvZsTzzxMCnY4jnBJ9f5Pa3l5QVUrZLGPSad4vFDb4zewwxPN9ApnmB3KBiG6AqBfgBQEt8jpY5TiMSSQohCG98nopg0B+0bd/0CId/yopS6ArCqbUiTcUBUsyxouI5jDAm4UCIxIJpmWztDoORcQUthpdxwsC5ufzqMCEVIp6VWW5ZXFvWxutskyjKwoJCYXtlNnHlExGsEcdh05JtArCkEFSOTTiGfy1pYWVlpyjLJvjCUXoIBU9L1ZKVcOQpMyWSr5PSlUZI/dZlGgVEAuEZ1kEwGv5PAYCQhtNcKtKJlku6/w2gO+j+T4ZRWGVI2ZUPNXRQVme11a5Dw/hjBV5zqNFX/Hl2EUQWRd9s7goSneB9y1LyHTI41suS4iLNCFrXqCfVWTihmweR8i0yKKgsYxY8KyK5yvNQ2Qn0LfnCFLmXNOY9i9w/LBesuULY+2uGBM3KpEgqWmMTacxVJWUbPAUPY9eGXWZ8j2Ry+v/eCAb6DXHNNmtgiR134UXYh18MADhrFn8/qqrmLh27af7YgPYyWedRa8cegHw6uTJA273zM47U6Uom3T8AH+u4Bhsju21cCHhl78cP650/uPuvHOD7c+++25S8oY48I03GNPWRjhrFv4BB+AceCDHPvtszDgGeOC00+JpaNskEgzSdYZrGsN1nf2XLaPz8MPpPOww9sjlyCkKtYbBME2jXlGoV1XGJhKMNAxGJxJMSKcZZppkEVFhVlFIAlXAcFnzNxA9gihry8qyDfI5FahXVaoUhSGaRhpx7eTk6xPTaabIfztKmeW4Fiz/RdmILv8flUoxSFXJKgoNEq8fhgLf3uq6rLQs3isUaJWQyBAxNEVVVZJSV75GYugHmyaDDAMN4mlpI02TM0eO5OXubv7R1hbrx6uqSlZV2S6dFouOojC9qoo6TWNaOs2EZJI9q6sZlUgwxDTZNpXCUFUxPzqRIFlxrpKKQp38rJGJBHtXVzNBophGp1JioZHnKbr/anUdHYTYHQLdZSCcaEr2w7Kaxi7V1WybSmECNaoa193T8rM1eRyVZiAi8yhKj34DFZHhlWVZuL+pcl8phJZVVlUZaZqkgCyC7Z2Rn51E1PcTwLhEgmokIq/is5Cfn5LHkwhDEmFIjapiKELW+V9hShhuiGj5vG2XXXYJX3/99S2yrwX5PN9dtCieRZvRtFgCufiR7xZ1eSUMCWQU/ON77+Wym24i/cQTfbYzHQf7K1/Z5L5+/Y1v8PN77tms49/t+ut5bfJkrrnmGn70wAObPtZ58wB45+STmbpiBf9x6aX88vbb2f2DD/psN/bOO1k5fDjBrFkAzJs+nVmysdtnf3PnkrJtSgNwAyptc76XMm8eofzcSjv00kuZM0AZLLKmujqGSbYzgDF3LvW9vRSrq3FZX7N3KvadefRRSqkUe7z7LoGq8tqUKXGEpiJuVhVIdHVx1HPP8YcjjujzmSlE1lHpEAwGZmxHjeaBrE5VGZpIUKVpvD5AFhKZiSDATUyn+aBQoCiPNcV6DSdVUWJJ8ZZymY6K+1WT+7Ar9ndYfT3vlUqssSzycpusqrJbLseEdJr7W1tpkeXOyHKqyglDhtBoi7Gm68plwcSV8hJJVY2Jkj7C4WkS/NA/ak4gpqNVaRqqotDpOLT7fgwZ7n8uIice1e0jixy2geDsDDFNqjWNt/N5LAb+TTbHIlDGJzETiUTq93xGUVBlP2hT7jy6H8wnn6Q6mWSP6mqumjDhE5G8FEV5IwzDXTb7jXwBI/8I159SVao1jZSqslMuJ2qv/baN4GSVFuy/P/4BB4gHYchV111HynEIZ80inDWLpMSZ3/Tb337ksWyu4wd4TUbvUYkE4PaDDuLks8/e6HumrlgBwDZtbZx4zjmcdsYZfV5fOXy4kMG98koADr/kEt4dO7bPNvWPPUatoqAm+3c0NrT/kVIRH8eywNyddtrg+U05fqCP4we46ppraD7iCPKzZjG6s3O98mmFFQ85hO7/+A9ePOMMXj79dKpLJcG2DkPqe3oECgZoOfJIrr/6aub/4AeAcDA6IgVP0vemiJxMtHhUsX4RiSzJ+og+jYgEazUtbuz1NwPBFzEQ3IjVUqBORzjPqL9Uq+tiPKic8Vq52GhAjYz2s0CtpolmtO8zNplkRDLJEE1DA0Ylk/R4Hs93d1Pud94yisLIRIJRyST71NQwOZ1Gk5lAVpK9PNkbyWkaJusX04ymURPxNuR5qDMMRiYSgnwn9Y+irCnB+sw5itYzipCB0BSFnDx/1VRE16rQZKrRNCalUnxryBBGmSY5mTVF+66Msjdlivz+1fKY+1vk2KN/G7OL//Qnwlmz0EPB+t6hsZGM7IcQhoSzZnHCk08yuLOTK/74R4Z2dPDrP/yBYRV9tTFNTTiScf28HDj1edoXrubv+D4fSKyth+j2R9ro/SO1EKHa+T+33cbvjziC7ooSihIEnDtAyeK1736XP37ta5zYLxPY0nbfPvtw2j/+AcDsc84hBG65/HJ602mqSn1jjhk33shbp57KrQcfjG2aLB05kusqavBRE+ypnXeOs4VpN9/M/3vggXi7zgGc/qk/+xk3/va33HTooZwikTz7XHUVhXSa7KOPovk+N115Jcc+99xGv0cJ2P83vxkw+t8cO+3BB+O/Fx91FOPvuIOpy5dvsF11cX1+19GvjPXK5Ml89+c/jx/vWlGq0xFEsDwDR4QBIppLsmFUVxmxeoh69AdSG2agffWpT4cheBvmBgoCJebDgK/7CDXTQFHEtS75Cq/n80LRNQxj1vN7pRIppL5U/2MPQ7o8j6npNHO7u3mqowMLeLtYFM1k26Yg31uuyBhKsoEZRfQRbLbo+/TIOn/JF2qrcZbW/zwBTgXpMvreJQQjF4Ag4PVCgYyi8HahIKCoEv3Vf5Lex7FINbdrI68PVAYaaJufSt8wc+FCbr38csavW8dtBx/Me6NHUyWvwdsvuyx+zy9kIOhWwKVHtbbiaRorBg3ilqameHrZ52VfvMjf8xiUTFKnaRjIiEDW+/tHigAX3nor/3X77bQcdRTbrVkTP3/Ms89y3DPPbLD9DitX8vsKx7olbY9rr43//onU0Dn4iitIIpzT/r/7Hdv1YwEDLJgwAWXePGxz/Tc84qKLPvLzrv/61xl8//1MueWWPs/vdc01XDh7NjcddhjD//53fnf00fFrz++4IwDFVIrebJblAwhSvTFhAgC7/uEPcZ13S9uyE07ggfPP36z37P7BBxsgoNLAMF2nXhUzixs0jXp14COOSkj9zUQsCjXAIE2LRQWjCHlzLMpooj5CRDgcaLsqXcy+rZY1cB1ASir4QSDKSvL9pqaRUVVqWd97iI5dCQJub2lhXnc3HoKVHslrI++bKKupUZS43h31LobqOilgXDLJSDkHoM4wmJ7NkgFq5Xsqo36AYRIRNMww2MYwSLK+hh9ZJMtRkoTCXun4o6w9qq0nGTiTB8hYFv847zzSsrZuAqPa2rjquuvQNgKzVoKACWvW0Hj00cx+/HFAkCcbK+4FgBfOOIPx69YBMPvxx/nVDTfwyzvuGHCfAOf89a/x30/9/Od8eMIJnDpnDlYQsOxzrv1/4SL/sckkludR3djIqhNPpPbhh2mpeH382rUs/fa3+fn3v8+V3/xmnx+qEsI4rLOTKatWfeTn1f3jH3QefviAr/3lwAP5zbHH8vYpp/R5/rtnnskFf/kL3dks05Yvp/rhh/n6Cy/wcgUr1tP1OEqPbO706QCcfcopfRi0A9nikSM/8tgB2mpraaut7fPci1On8uLUqQA0NTRQW9F87W8XnnQSZ991F/MnTWK3RYs4/YwzuOGww/D+BWPpPo5dcNttfR6XgOePOor79tmnDynuG3Pnste77/KjH/+4z/ZlNrQoWoxQLPSrqW+ORdFsZQQ6kHvygHUV4nuRtW+kh1eS/JVKsT4QWYzl+9xTUY6IZgj0lzZxATMMN4iOmyQjek25jI8oD9m+T4uqiqyh336i75j3fVrkZyXl/vuf38rjHSi6j/ZV7ve40n55++187aWX+N111zF/8mRsw+DEJ5/kwDfe4PinnuL0M87gbxWABRDl38huveIKfnzffcyQ8iZ/ufTSAT7lk1tZlqc/7zm+X7jIf1giwT41NSw57jiSrss5/Uo3SyUG/9c33MAYuWJHNrOiUVoJk9yUdckB2JEp8+Yx7o47GH/HHcw+91zekexZgLfHjkWZN49bDj2U0ffcw44334wybx692Sy3SXTQx7Erjj+eF6ZN2+Q2i0aN+tj762/9lYMGiu4js00TZd483pTRvq+qAzr+5cOGbfIzp958M9lHH+3z3EN77PGxjnfsnXfyq298g98cc8xHbpvrF13ddumljGpt5af33kt1oQBhyJHPPcfdF13E6VGpKQzZZdGiGOI5vK2tD3S3f915U2ixLWmb8zmVaqufxKLMQmN91lB5DBHTVQUC3xfSG1IpcyDTWD8GNGpuJ4GB1ag231TE73TrZZdx9l13AXDqnDn86coruf2yy2joEYDtQT093HPRRSw68UQSjoPpOPz9ggs22N+MCl2rbz/11BY6SmH1ts1h9fWfu6rnZ+L8FUU5WFGUxYqiLFMUZeOdys/Air7P6xWR6vm33w5A0rYZ3K+JuPxb3+rzeKAa8qZs76uvBuCks84C4AUZjS8fMYIPR4wQG1WIsH1Hbve5mKKgzJu3Qfbwcax/7FhOJD5yX+9tuy0A7RthKs6UukV/23ff+LkLTjqJY88/H+Opp1g4dizFVIpRd98dv75yyBAO+tWvsCto73f1i9AAVgwfzlk/+AEXfAxGc2RrGxoAOLHiRu4+7DB+8NBD3HfhhfFzB772Gl978UVe++EPmS37PI3HHsucc8/lLJnCR+crIvhsDN2zubbnu++y57vvbvT1zUG8OHL7T8olj/gq/ZE20f7KiMynBHTIvx0GPkbd89AkYzYAQs9j/PLl7Dl/PjMXLOD92bMxXHeD4AygvqenzyL887vu4rQHHoAwZHBnJ4br8p/33MOIlhYajz2W2U8+OeD3mdFPpHC7NWs47cEHmbR69UdCore0tcgZvp835HOLQz0VRdGAJcCBwFrgNeC4MAzf39h7tiTU86nOTv7fokUs3XPP+Ln+sMGNWWNDAyP6sVwvO/74PnW6Sks+8QS2aVJVKLDkxBM55oIL4pp4pW23ejUnPf4455x66mZ+m49nHxe2FtVEPy1MbsBj8H2+8tprPDabZtjMAAAUhklEQVRzZp8Fr9J04KIbb+Tsu+7i+PPO464IVdXPTnn4YW787W+55eCD+e5ZZzG6uZmVxx3H47vuyvWHH85Dv/wlIMpnb02YwFsTJ8bvHb92LWoQsPOSJfz1kkvi598fPZrtK8p49Q8+SEc/qOfG7BennsqvbrwRgIYHH6S94n0fd3HVfJ9xjY2UTZOO6mqmrFjBq6edxqGXXsqjX/rSBtvX9vbG5UT1mWcIVRXCkGuuvZYfPfAA6ccew5JN+m2bmmiuq6O8ERVXgM7DDqO2UPhEwcCWttdPPZWxTU3USXLipsAAe15zDS/JEmRVoUDPYYcBsONNN/Upp967zz6fu9OedNttLJYZ9uYCGpR58xje1sZlN93E//vZz9impoZrJ07kwLq6zdvPvxnUczdgWRiGy8MwdIC7gYGL4p+BJRSFzmJfRP9HOf5nZswAiB1/UOG8HtttN4bedx/b3nUXI/72N46pSAmjBmtvNsvQ++8f0PEDLB416jNz/LD5SIfP5Bg0jcd2332jjh9E5Pjfs2dzxumnc88mbpYeOQM3QjWtGjqUmdddxxEXX0xCokDu3Wcfbjn00D6OH2DZNtuwZNSoDRaW/X/zm/jvUXffTWe/ct2mLHL8QB/HD9Da7/Go5maGVvSOvvnMM5xx7714BxzA4tmzWXXccRQOOYRXZX/h5l//esDPrFyoBksYYG0+H3M/bpKw3YbublYcfzzWwQczZBPXeW1BIPKNjykguKUs3S+azZZK7Lx0KbWFAlM//HCD1/vbi2ecAWHI0I4O3qvI7Pr30Q5/8cUtd9AbsS/9/vd9Hi+uKK2eLY/HHCDTeErOxojKktNvugmAdYMGMfvccykmk4Rh+IWo+Y8A1lQ8Xiuf62OKopyqKMrriqK83lYxtOTTmh2GbCMvqNJGIqFHZ87kSinKtmjkSA6ocAwA2ty5PL3TTjw3bRrP77gjLXV1rBo6lHWDBnHvfvux3+9+N+CP/EWxz1JbsJxIcO1RR8UkuoFs4ZgxALw8ZUr83Pztt8c2TZ7cZRfeHjuWC6Xq6Kbs19/4Bud+97so8+bRXF/PnbKJ11RfD4oSl+1g49fKR9mgnh6Sth3zQFYddxxNRx/N5TfcwIwlS7jr4ou5ehP9o4dlX6O+p4dUucyENWsgDDlFSn8DfHPuXB4+5xyuv+qq+Lm3ZI/l1Irtmo86asDP0Cugol9//vn47wv//GfCWbMY1dwsnghDeg49lIv/9Ke4tDKQzTn7bP4geS6a7/P3Cy7g8AEkPf70q19RPOQQ9nrnHa669lpOfPxx8hXw23e+9z2KhxzC0wPwQCot/PKXaTr66AG1pyIzNoLaeWbGDJR583h/9OiNvnf43/8+4POrhgxh6s03x49fmTKFqkceYfwdd7BTxWAjEH04Zd48XMOgM5fDr0CMfeess7hnv/248KSTUObN4+3x4zf4rDHJ5Ode8/8syj5HAweHYfg9+fjbwMwwDE/f2Hu2ZNlnTlsb5zz2GO/Mns3x553XJ/UHEfWtGTJkg/dFadvNX/0q3/vFL7bIsWy1T25jGxtFo3kTmcSWsOh3H4iJfOtXvsJJnzGfA2Dan/7EO9/73ma/r/rhh+MySGSHXnopT+66K/effz6Hvfwyr223Hb859ljultDfe/bbj7p8nkBR+ErFPTfmr3/l2Z/+lNEt67FxtQ89hO77zFi6lJenTGHXRYtwDIMX+pEIK22HW27hPbl4R+fz+alT2XsTvYvP0rKPPkoxlWJIZ+cGi+OTu+zCL77/feGMwxD7oIMwPY+zTzmF6mKR/znxRJKOQ9fXvgZ8/BIfAGFI01FHccjll2+QnQ5kPxo6lGsmTdqs7wafruzzWeDxGoFKnOE28rnP3P7Z1cWv1qwhJ1PcnkyGOw44gBPkDNtJt902oOMHuPiEE/jlHXdQ39t/mOL/LesvPvWvsuUjNkgWPxN7furUOC2PpKoj+87ZZw/o/A+75BIe2WOPza7z/vi007jmqKP66CABn8jxAxs4ftiQOb3r4sWx4wf4RgVzvNJWHH/8Bs9FTm9zbOHJJ/Pngw/mOxIbD2zg+O+eNYtv9ocxz5jBszvuyP9UCBr+4Kc/5Y+/+138+JJvfYs5u+/OjKVLOf6ZZzjxnHNYPmLEBr/DFd/8Jvu/+Sb/nDaNooymW+rqYud950UXcfzcuRx62WXrkWmKQmIAFE/ZNPFVdbNY7dH+ht1//8faVAXMfwE0+rOI/HVEw3d/hNN/DTg+DMP3NvaeLRH5/7Ori2PefZfWIOCo557j3gsvZPpNN/H2uHGc9Pjj3LvvvhTS6Y2+v7pQ4M6LL+b//eQnrO43iGSr/d+wQ15+mTnnnktPJsPg++/HMU2u+OMf+cU993Di2Wdz+U03cd0RR3DpCScAQpK69cgjP3K/lc1ZgGPnzuWej0HCA2itqYlr/pG9PXYsO1Yg0/7wta9x/eGHDzj289/RLj/uuBh+GdlRF17IP/bai22bm/nnj3/M8I4Oah96CE/TmPXWW6I8tpEssHjwwaRtmxVDhzK2334HMs33qS4U6PwXaOgPZApw04QJfPcTBDyfJvL/TITdFEU5BLgKAee9JQzDSza1/ad1/l2uyy+WLeO2lhZc4Jw77uBSiRsvfs51tK32v9eUIGDeT3/KSWefzcqP4CVEpvk+4xsbWTl0KLlSSUBdFQUlCDjihRfozmaZ16+mnbEsCocc0gdJVkgmyT32GEnbZtdFi/jnT37C/ldeydydd+Y/XnqJ0S0t/P6aa3hojz04/zvfYYFsML46aRK7/+EPAExZsSKe5fzozJmc+p//iatptBx1FH/bd98BZTj+84c/5Dfy/QD600/zlfnzP1J7CWDpiBGsq6/n7/vtt1ms9y//5jcsGzGC3kyGbpm97HXNNTGxsKpQYKelS3lWAjE+ymryeX5y77389+zZAhX1v8zSwO3bb8+Rgwdv9nv/7Zz/5tqncf5drsv1jY1cv2YN62TT55YrruArr73GiHvv3ZKHudW22ha3fRYs4M5LLmH03XdvsglOGPKdxx7jwb32oquqivFr1/LPH/+YQy6/nAWy+QtwyU03cebf/kbVnDkxGk3zfXxVZdy6dVx+440sGD+eS044AS0I8DWNEW1tXHHDDfz37Nkslczwi26+mX9Om0bKtqkpFHh1++3pTae5/dJLWThmDD/50Y82OMTa3l5eOOMMtl+1ihsPPZRT58xh8q238sFJJ3HERRfxoJzuVvXII+QlouuEJ5/k9ssuQ3/6afxNff8vuB1RV8ctkydv9ijH/9PO/6rVq/nN6tWslYgGzffxJMzv3wHTvNW22lYTVtlc32p9bXo6zd922IEJmyhND2T/bg3fz83uaW7m58uXxw3Kb8ydGze3PtyEJMFW22pb7fO3//zhD+nYDH7F/yUbISetfZ72v9r5X7xyJR4wrL2d3d9/P3b8XdksEwdQv9xqW22r/evst5Jbs9X6mgF8taFhs0s+n9b+1zr/XyxZwm733cfDt9/OthXY5L2vvvojRc+22lbbalvt38VcwN/I/PDP0v7XOv85XV2Mra3l/7d37jF2VHUc//xm5j722X22blsKLQkIDVEQ5SHIIyi1EIn/GIh/gOgfiiG+ogFJjPofrX8g8QHGR1ARQURNmhCixBgSkhJAW0rp0tIW6KZ0S2Ff3b33zsw9/nHO7N7d7m67s/fu3eX+PsmkZ86ZO/Ptd+f85t5zZub3/ObN/GbrVo709vL0ZZdxbIHvxlguJPfXJ2+FXMhD+E3Ybw8T2DyqJZdKLnnmMUmJl8zuVGuWZ75UhoqinJ4kJ8FbpTNJI1P9Y69IbursZPuVV7Jjntf+CjbZ87hLeL3Qd9u0ex4XNDezb2yM4TP8TJrcoFlsntLkXgcDjLssTslbipKk0klGqYQuz2N9Pk9PENA/MYEBRsOQjAjiLgJtFfsOy2XemyPD1JnS5nTlsG9vzDJ/zlJFqQdJkvjZcjAkJOdwvfCArOdxXR2eOVixwX+be2R6+yyvfW0Frly1ii+sXk3BGDIijEYRo+UyGaB/fJzQGHzgUKFAyRjGoojhUon2bJaLWlpYl89zfnMzW7q7ebtQ4BcDA+waG6MYx6zJ5VibzbKhqYmeIOD5oSFOGsM17e14nsfRiqt4RxAQuGOOuoC+oamJQIThMKQvn+eC5mbynseqILDvV4ljfBFGosjmb41jNmSzbGxqYiSK2D02xpuFAh9uaeGajg7afJ/2IGA8jnnl5Ek63H4GikU6MplT9n0iDNl78iTj5TItnke77/NOqURvNstgqcTeiQnW+D59+TxlY2jxfd4qFjHA1e3ttGUyDIUhxXKZs/N53osi3g9DTkQRxhjOyed5fXycgWKRi9raOCuX4+DEBLExnDSGtS570+ODg7w2NkYM9GQyeCIU4hjPPcwTlcsEnse5zc2szWY5VirZHKnAkVKJ1UHAiSji3TDk/KYm1ubz7Bkd5WipRG8mw1AcMx7HbMjlMMCxKCLrcsYOR9HksbKeZ9tLJUrYi1uA/VVTxF5wW4GM75PxPALPIyqXKbsUiBH2XfQFpqdJzOHy9GJ/JeVF6MrlyInwTqGA73lkfZ/xMLSZtnyfQZcofXUuB8ZwqFQidPtqAzpzOcajiGGXMKYnCMj7PgPFIiVssPOwKSkDz2MkjidTJoZOR9LpkxHmJDNWK4AII8ZMZhRL8gCUsV8i+nI5jpVKHA9DIqayeTV5Ht25HIVy2b4qIY4ZiWNW+T6+7/N+qUQRaPE8NuXzHA9DfJc/GGymrrhcpuwyh4kI67JZRuKYojF8orWVAnC0WGQ4DJkolyeHS0rYL2pgXyO9IZulOZNhbTbLVe3tvDw6ynNDQ4xUvP+nOwi4uK2N9iAgNIbDhQKtQcBIGPLc8DAe0BUEDMUxPUHAxqYmWnyfSITAGCIRWkXY787zQIThOKbZ9+n0fUbjmEEXB7qyWTp8n+4gIPA8fM+b7HcT5TJbu7u5qbf3lDhWa1b8rZ6KoiiNynJ7pbOiKIqyzNHgryiK0oBo8FcURWlANPgriqI0IBr8FUVRGhAN/oqiKA3IsrjVU0SOA2+edsPZ6QHmTu5ZX1RbOlRbOlRbOlaytrONMakeElgWwX8xiMiLae9zrTWqLR2qLR2qLR2Nqk2HfRRFURoQDf6KoigNyAch+P+q3gLmQbWlQ7WlQ7WloyG1rfgxf0VRFGXhfBC++SuKoigLRIO/oihKA7Kig7+IbBGRfhE5ICL3LMHxzhKRf4vIXhF5VUS+4eq7ROSfIrLf/dvp6kVEHnT6dovIJRX7ut1tv19Ebq+iRl9E/isiO9z6RhHZ6TQ8LiJZV59z6wdc+zkV+7jX1feLyI1V1NYhIk+KyD4ReU1ErlgO3onIt9zfc4+IPCYi+Xr6JiK/FZFBEdlTUVc1n0TkYyLyivvMgyIugUJ6bdvd33S3iPxNRDpO58lcfXcu39Nqq2j7jogYEelZLr65+rudd6+KyLaK+tr7ZoxZkQs2h8QbwCZs3oldwIU1PmYfcIkrtwGvAxcC24B7XP09wP2uvBV4Gpsr43Jgp6vvAg66fztdubNKGr8N/AnY4dafAG515YeAr7nyXcBDrnwr8LgrX+i8zAEbncd+lbQ9AnzFlbNAR729A9YBh4CmCr/uqKdvwKeAS4A9FXVV8wl4wW0r7rOfXaS2zwCBK99foW1WT5in787le1ptrv4s4Bnsg6Q9y8i364B/ATm3vnopfatZoKz1AlwBPFOxfi9w7xJr+AfwaaAf6HN1fUC/Kz8M3Faxfb9rvw14uKJ+2naL0LMeeBa4HtjhTtJ3KzrmpGeuM1zhyoHbTmb6WLndIrWtwgZZmVFfV++wwf9t19kD59uN9fYNOGdGoKiKT65tX0X9tO3SaJvR9nngUVee1RPm6Lvzna+L0QY8CXwEOMxU8K+7b9iAfcMs2y2Jbyt52CfptAlHXN2S4H7uXwzsBNYYY466pneANa48l8ZaaX8A+B5TaYS7gSFjTDTLcSY1uPZht32ttG0EjgO/Ezss9WsRaaHO3hljBoCfAG8BR7E+vMTy8S2hWj6tc+Va6bwT+604jbb5ztdUiMgtwIAxZteMpuXg23nA1W645j8i8vGU2lL5tpKDf90QkVbgr8A3jTEjlW3GXnqX/P5ZEbkZGDTGvLTUxz5DAuzP3l8aYy7G5oCfNk9TD+/c2Pkt2IvTWqAF2LKUGhZKvc6x0yEi9wER8Gi9tQCISDPwfeAH9dYyBwH2F+flwHeBJxYyj7BYVnLwH8CO5SWsd3U1RUQy2MD/qDHmKVd9TET6XHsfMHgajbXQ/kngcyJyGPgzdujnp0CHiCQ5uyuPM6nBta8CTtRIG9hvI0eMMTvd+pPYi0G9vbsBOGSMOW6MCYGnsF4uF98SquXTgCtXVaeI3AHcDHzRXZzSaDvB3L6n4VzsRX2X6xfrgZdF5EMptNXCtyPAU8byAvYXe08Kbel8SzMeuRwW7FXzIPaPm0x+bK7xMQX4PfDAjPrtTJ+M2+bKNzF9UukFV9+FHf/udMshoKuKOq9lasL3L0yfCLrLlb/O9InLJ1x5M9Mnmw5SvQnf54DzXfmHzre6egdcBrwKNLtjPQLcXW/fOHV8uGo+cerE5dZFatsC7AV6Z2w3qyfM03fn8j2tthlth5ka818Ovn0V+LErn4cd0pGl8q0mQXKpFuyM/evYGfD7luB4V2F/bu8G/ueWrdgxt2eB/djZ++RkEeDnTt8rwKUV+7oTOOCWL1VZ57VMBf9N7qQ94E6Q5M6CvFs/4No3VXz+Pqe5nwXc0XAGuj4KvOj8+7vrXHX3DvgRsA/YA/zBdbq6+QY8hp1/CLHfDr9cTZ+AS93/9Q3gZ8yYhE+h7QA2cCV94qHTecIcfXcu39Nqm9F+mKngvxx8ywJ/dPt8Gbh+KX3T1zsoiqI0ICt5zF9RFEVJiQZ/RVGUBkSDv6IoSgOiwV9RFKUB0eCvKIrSgGjwVxRFaUA0+CuKojQg/wfGaODmIhSNSQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import json\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "from collections import deque\n",
    "\n",
    "\n",
    "fp = './FlappyBird-v0/DQN-lr_1_e-3/openaigym.episode_batch.0.11820.stats.json'\n",
    "\n",
    "data = json.load(open(fp))\n",
    "\n",
    "rewards = data['episode_rewards']\n",
    "plt.plot(range(len(rewards)), rewards, '.c', alpha=0.3)\n",
    "print(np.argmax(rewards))\n",
    "print(rewards[np.argmax(rewards)])\n",
    "\n",
    "\n",
    "win_deque = deque(maxlen=50)\n",
    "avg_scores = []\n",
    "\n",
    "num = len(rewards)\n",
    "for i in range(num):\n",
    "    win_deque.append(rewards[i])\n",
    "    avg_scores.append(np.mean(win_deque))\n",
    "\n",
    "plt.plot(range(num), avg_scores, '-r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ffmpeg version 2.8.14-0ubuntu0.16.04.1 Copyright (c) 2000-2018 the FFmpeg developers\n",
      "  built with gcc 5.4.0 (Ubuntu 5.4.0-6ubuntu1~16.04.9) 20160609\n",
      "  configuration: --prefix=/usr --extra-version=0ubuntu0.16.04.1 --build-suffix=-ffmpeg --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --cc=cc --cxx=g++ --enable-gpl --enable-shared --disable-stripping --disable-decoder=libopenjpeg --disable-decoder=libschroedinger --enable-avresample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libmodplug --enable-libmp3lame --enable-libopenjpeg --enable-libopus --enable-libpulse --enable-librtmp --enable-libschroedinger --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxvid --enable-libzvbi --enable-openal --enable-opengl --enable-x11grab --enable-libdc1394 --enable-libiec61883 --enable-libzmq --enable-frei0r --enable-libx264 --enable-libopencv\n",
      "  libavutil      54. 31.100 / 54. 31.100\n",
      "  libavcodec     56. 60.100 / 56. 60.100\n",
      "  libavformat    56. 40.101 / 56. 40.101\n",
      "  libavdevice    56.  4.100 / 56.  4.100\n",
      "  libavfilter     5. 40.101 /  5. 40.101\n",
      "  libavresample   2.  1.  0 /  2.  1.  0\n",
      "  libswscale      3.  1.101 /  3.  1.101\n",
      "  libswresample   1.  2.101 /  1.  2.101\n",
      "  libpostproc    53.  3.100 / 53.  3.100\n",
      "Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'play_1e-3/openaigym.video.0.11919.video000001.mp4':\n",
      "  Metadata:\n",
      "    major_brand     : isom\n",
      "    minor_version   : 512\n",
      "    compatible_brands: isomiso2avc1mp41\n",
      "    encoder         : Lavf56.40.101\n",
      "  Duration: 00:04:39.47, start: 0.000000, bitrate: 109 kb/s\n",
      "    Stream #0:0(und): Video: h264 (High) (avc1 / 0x31637661), yuv420p, 288x512, 106 kb/s, 30 fps, 30 tbr, 15360 tbn, 60 tbc (default)\n",
      "    Metadata:\n",
      "      handler_name    : VideoHandler\n",
      "Input #1, png_pipe, from 'palette.png':\n",
      "  Duration: N/A, bitrate: N/A\n",
      "    Stream #1:0: Video: png, rgba(pc), 16x16 [SAR 1:1 DAR 1:1], 25 tbr, 25 tbn, 25 tbc\n",
      "Output #0, gif, to 'dqn_agent.gif':\n",
      "  Metadata:\n",
      "    major_brand     : isom\n",
      "    minor_version   : 512\n",
      "    compatible_brands: isomiso2avc1mp41\n",
      "    encoder         : Lavf56.40.101\n",
      "    Stream #0:0: Video: gif, pal8, 288x512, q=2-31, 200 kb/s, 5 fps, 100 tbn, 5 tbc (default)\n",
      "    Metadata:\n",
      "      encoder         : Lavc56.60.100 gif\n",
      "Stream mapping:\n",
      "  Stream #0:0 (h264) -> paletteuse:default\n",
      "  Stream #1:0 (png) -> paletteuse:palette\n",
      "  paletteuse -> Stream #0:0 (gif)\n",
      "Press [q] to stop, [?] for help\n",
      "frame=  150 fps= 22 q=-0.0 Lsize=    3650kB time=00:00:30.00 bitrate= 996.8kbits/s dup=0 drop=746    \n",
      "video:3648kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.053561%\n"
     ]
    }
   ],
   "source": [
    "vp = 'play_1e-3/openaigym.video.0.11919.video000001.mp4'\n",
    "# !ffmpeg -y -i {vp} -vf palettegen palette.png\n",
    "!ffmpeg -y -i {vp} -i palette.png -filter_complex paletteuse -r 5 -ss 00:00:00 -to 00:00:30 dqn_agent.gif "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Filesystem      Size  Used Avail Use% Mounted on\r\n",
      "udev            3.9G     0  3.9G   0% /dev\r\n",
      "tmpfs           799M  2.9M  796M   1% /run\r\n",
      "/dev/vda1        40G  5.7G   32G  16% /\r\n",
      "tmpfs           3.9G     0  3.9G   0% /dev/shm\r\n",
      "tmpfs           5.0M     0  5.0M   0% /run/lock\r\n",
      "tmpfs           3.9G     0  3.9G   0% /sys/fs/cgroup\r\n",
      "tmpfs           799M   24K  799M   1% /run/user/0\r\n"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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